hexuan21 commited on
Commit
b795f9b
·
verified ·
1 Parent(s): 2db4dcf

Upload folder using huggingface_hub

Browse files
This view is limited to 50 files because it contains too many changes.   See raw diff
Files changed (50) hide show
  1. .gitattributes +5 -0
  2. README.md +59 -0
  3. adapter_config.json +138 -0
  4. adapter_model.safetensors +3 -0
  5. added_tokens.json +3 -0
  6. all_results.json +8 -0
  7. chat_template.jinja +47 -0
  8. checkpoint-1000/README.md +202 -0
  9. checkpoint-1000/adapter_config.json +138 -0
  10. checkpoint-1000/adapter_model.safetensors +3 -0
  11. checkpoint-1000/added_tokens.json +3 -0
  12. checkpoint-1000/chat_template.jinja +47 -0
  13. checkpoint-1000/optimizer.pt +3 -0
  14. checkpoint-1000/preprocessor_config.json +29 -0
  15. checkpoint-1000/processor_config.json +4 -0
  16. checkpoint-1000/rng_state.pth +3 -0
  17. checkpoint-1000/scheduler.pt +3 -0
  18. checkpoint-1000/special_tokens_map.json +33 -0
  19. checkpoint-1000/tokenizer.json +3 -0
  20. checkpoint-1000/tokenizer.model +3 -0
  21. checkpoint-1000/tokenizer_config.json +0 -0
  22. checkpoint-1000/trainer_state.json +1434 -0
  23. checkpoint-1000/training_args.bin +3 -0
  24. checkpoint-1500/README.md +202 -0
  25. checkpoint-1500/adapter_config.json +138 -0
  26. checkpoint-1500/adapter_model.safetensors +3 -0
  27. checkpoint-1500/added_tokens.json +3 -0
  28. checkpoint-1500/chat_template.jinja +47 -0
  29. checkpoint-1500/optimizer.pt +3 -0
  30. checkpoint-1500/preprocessor_config.json +29 -0
  31. checkpoint-1500/processor_config.json +4 -0
  32. checkpoint-1500/rng_state.pth +3 -0
  33. checkpoint-1500/scheduler.pt +3 -0
  34. checkpoint-1500/special_tokens_map.json +33 -0
  35. checkpoint-1500/tokenizer.json +3 -0
  36. checkpoint-1500/tokenizer.model +3 -0
  37. checkpoint-1500/tokenizer_config.json +0 -0
  38. checkpoint-1500/trainer_state.json +2134 -0
  39. checkpoint-1500/training_args.bin +3 -0
  40. checkpoint-1795/README.md +202 -0
  41. checkpoint-1795/adapter_config.json +138 -0
  42. checkpoint-1795/adapter_model.safetensors +3 -0
  43. checkpoint-1795/added_tokens.json +3 -0
  44. checkpoint-1795/chat_template.jinja +47 -0
  45. checkpoint-1795/optimizer.pt +3 -0
  46. checkpoint-1795/preprocessor_config.json +29 -0
  47. checkpoint-1795/processor_config.json +4 -0
  48. checkpoint-1795/rng_state.pth +3 -0
  49. checkpoint-1795/scheduler.pt +3 -0
  50. checkpoint-1795/special_tokens_map.json +33 -0
.gitattributes CHANGED
@@ -33,3 +33,8 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
 
 
 
 
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
36
+ checkpoint-1000/tokenizer.json filter=lfs diff=lfs merge=lfs -text
37
+ checkpoint-1500/tokenizer.json filter=lfs diff=lfs merge=lfs -text
38
+ checkpoint-1795/tokenizer.json filter=lfs diff=lfs merge=lfs -text
39
+ checkpoint-500/tokenizer.json filter=lfs diff=lfs merge=lfs -text
40
+ tokenizer.json filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,59 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ license: other
4
+ base_model: google/gemma-3-4b-it
5
+ tags:
6
+ - llama-factory
7
+ - lora
8
+ - generated_from_trainer
9
+ model-index:
10
+ - name: gemma3-4b-it_eqa_lora_sft
11
+ results: []
12
+ ---
13
+
14
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
15
+ should probably proofread and complete it, then remove this comment. -->
16
+
17
+ # gemma3-4b-it_eqa_lora_sft
18
+
19
+ This model is a fine-tuned version of [google/gemma-3-4b-it](https://huggingface.co/google/gemma-3-4b-it) on the energy_qa_alpaca dataset.
20
+
21
+ ## Model description
22
+
23
+ More information needed
24
+
25
+ ## Intended uses & limitations
26
+
27
+ More information needed
28
+
29
+ ## Training and evaluation data
30
+
31
+ More information needed
32
+
33
+ ## Training procedure
34
+
35
+ ### Training hyperparameters
36
+
37
+ The following hyperparameters were used during training:
38
+ - learning_rate: 0.0001
39
+ - train_batch_size: 1
40
+ - eval_batch_size: 8
41
+ - seed: 42
42
+ - gradient_accumulation_steps: 8
43
+ - total_train_batch_size: 8
44
+ - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
45
+ - lr_scheduler_type: cosine
46
+ - lr_scheduler_warmup_ratio: 0.1
47
+ - num_epochs: 1.0
48
+
49
+ ### Training results
50
+
51
+
52
+
53
+ ### Framework versions
54
+
55
+ - PEFT 0.15.2
56
+ - Transformers 4.52.4
57
+ - Pytorch 2.7.0+cu126
58
+ - Datasets 3.6.0
59
+ - Tokenizers 0.21.1
adapter_config.json ADDED
@@ -0,0 +1,138 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "google/gemma-3-4b-it",
5
+ "bias": "none",
6
+ "corda_config": null,
7
+ "eva_config": null,
8
+ "exclude_modules": null,
9
+ "fan_in_fan_out": false,
10
+ "inference_mode": true,
11
+ "init_lora_weights": true,
12
+ "layer_replication": null,
13
+ "layers_pattern": null,
14
+ "layers_to_transform": null,
15
+ "loftq_config": {},
16
+ "lora_alpha": 16,
17
+ "lora_bias": false,
18
+ "lora_dropout": 0.0,
19
+ "megatron_config": null,
20
+ "megatron_core": "megatron.core",
21
+ "modules_to_save": null,
22
+ "peft_type": "LORA",
23
+ "r": 8,
24
+ "rank_pattern": {},
25
+ "revision": null,
26
+ "target_modules": [
27
+ "language_model.layers.13.self_attn.q_proj",
28
+ "language_model.layers.11.self_attn.k_proj",
29
+ "language_model.layers.7.self_attn.k_proj",
30
+ "language_model.layers.15.self_attn.v_proj",
31
+ "language_model.layers.15.self_attn.k_proj",
32
+ "language_model.layers.26.self_attn.v_proj",
33
+ "o_proj",
34
+ "language_model.layers.7.self_attn.v_proj",
35
+ "32.self_attn.k_proj",
36
+ "27.self_attn.q_proj",
37
+ "language_model.layers.14.self_attn.q_proj",
38
+ "language_model.layers.6.self_attn.q_proj",
39
+ "33.self_attn.q_proj",
40
+ "language_model.layers.13.self_attn.v_proj",
41
+ "language_model.layers.18.self_attn.q_proj",
42
+ "language_model.layers.11.self_attn.q_proj",
43
+ "28.self_attn.q_proj",
44
+ "language_model.layers.19.self_attn.q_proj",
45
+ "27.self_attn.v_proj",
46
+ "language_model.layers.24.self_attn.q_proj",
47
+ "language_model.layers.22.self_attn.k_proj",
48
+ "language_model.layers.25.self_attn.v_proj",
49
+ "language_model.layers.26.self_attn.q_proj",
50
+ "29.self_attn.k_proj",
51
+ "language_model.layers.24.self_attn.k_proj",
52
+ "language_model.layers.25.self_attn.q_proj",
53
+ "down_proj",
54
+ "language_model.layers.20.self_attn.q_proj",
55
+ "language_model.layers.10.self_attn.v_proj",
56
+ "30.self_attn.q_proj",
57
+ "33.self_attn.v_proj",
58
+ "language_model.layers.4.self_attn.q_proj",
59
+ "language_model.layers.18.self_attn.v_proj",
60
+ "31.self_attn.q_proj",
61
+ "33.self_attn.k_proj",
62
+ "language_model.layers.24.self_attn.v_proj",
63
+ "language_model.layers.23.self_attn.k_proj",
64
+ "language_model.layers.17.self_attn.k_proj",
65
+ "language_model.layers.0.self_attn.q_proj",
66
+ "language_model.layers.10.self_attn.q_proj",
67
+ "29.self_attn.v_proj",
68
+ "language_model.layers.1.self_attn.q_proj",
69
+ "30.self_attn.k_proj",
70
+ "language_model.layers.6.self_attn.k_proj",
71
+ "language_model.layers.1.self_attn.v_proj",
72
+ "28.self_attn.v_proj",
73
+ "language_model.layers.4.self_attn.v_proj",
74
+ "language_model.layers.0.self_attn.k_proj",
75
+ "30.self_attn.v_proj",
76
+ "28.self_attn.k_proj",
77
+ "language_model.layers.9.self_attn.v_proj",
78
+ "gate_proj",
79
+ "language_model.layers.4.self_attn.k_proj",
80
+ "language_model.layers.26.self_attn.k_proj",
81
+ "language_model.layers.3.self_attn.q_proj",
82
+ "language_model.layers.20.self_attn.v_proj",
83
+ "language_model.layers.5.self_attn.q_proj",
84
+ "language_model.layers.8.self_attn.q_proj",
85
+ "language_model.layers.16.self_attn.k_proj",
86
+ "language_model.layers.12.self_attn.k_proj",
87
+ "language_model.layers.2.self_attn.v_proj",
88
+ "language_model.layers.6.self_attn.v_proj",
89
+ "language_model.layers.12.self_attn.q_proj",
90
+ "language_model.layers.17.self_attn.v_proj",
91
+ "31.self_attn.v_proj",
92
+ "language_model.layers.16.self_attn.v_proj",
93
+ "language_model.layers.20.self_attn.k_proj",
94
+ "language_model.layers.12.self_attn.v_proj",
95
+ "language_model.layers.3.self_attn.k_proj",
96
+ "language_model.layers.8.self_attn.v_proj",
97
+ "language_model.layers.3.self_attn.v_proj",
98
+ "32.self_attn.v_proj",
99
+ "27.self_attn.k_proj",
100
+ "language_model.layers.5.self_attn.v_proj",
101
+ "language_model.layers.10.self_attn.k_proj",
102
+ "31.self_attn.k_proj",
103
+ "language_model.layers.16.self_attn.q_proj",
104
+ "language_model.layers.22.self_attn.v_proj",
105
+ "language_model.layers.9.self_attn.k_proj",
106
+ "language_model.layers.2.self_attn.q_proj",
107
+ "language_model.layers.19.self_attn.k_proj",
108
+ "language_model.layers.2.self_attn.k_proj",
109
+ "language_model.layers.23.self_attn.v_proj",
110
+ "language_model.layers.9.self_attn.q_proj",
111
+ "language_model.layers.14.self_attn.v_proj",
112
+ "language_model.layers.0.self_attn.v_proj",
113
+ "language_model.layers.21.self_attn.v_proj",
114
+ "language_model.layers.19.self_attn.v_proj",
115
+ "29.self_attn.q_proj",
116
+ "language_model.layers.15.self_attn.q_proj",
117
+ "language_model.layers.22.self_attn.q_proj",
118
+ "language_model.layers.21.self_attn.q_proj",
119
+ "language_model.layers.17.self_attn.q_proj",
120
+ "language_model.layers.11.self_attn.v_proj",
121
+ "language_model.layers.18.self_attn.k_proj",
122
+ "language_model.layers.25.self_attn.k_proj",
123
+ "language_model.layers.7.self_attn.q_proj",
124
+ "32.self_attn.q_proj",
125
+ "language_model.layers.23.self_attn.q_proj",
126
+ "language_model.layers.21.self_attn.k_proj",
127
+ "language_model.layers.5.self_attn.k_proj",
128
+ "language_model.layers.8.self_attn.k_proj",
129
+ "language_model.layers.13.self_attn.k_proj",
130
+ "up_proj",
131
+ "language_model.layers.1.self_attn.k_proj",
132
+ "language_model.layers.14.self_attn.k_proj"
133
+ ],
134
+ "task_type": "CAUSAL_LM",
135
+ "trainable_token_indices": null,
136
+ "use_dora": false,
137
+ "use_rslora": false
138
+ }
adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:14e9e7343d876dd5bfa1c7a89e5fb9c90e9aae4cc3e14dd5e546f880a54d0543
3
+ size 59675008
added_tokens.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ {
2
+ "<image_soft_token>": 262144
3
+ }
all_results.json ADDED
@@ -0,0 +1,8 @@
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "epoch": 1.0,
3
+ "total_flos": 1.3693762155471667e+17,
4
+ "train_loss": 1.6660522120908774,
5
+ "train_runtime": 6875.1124,
6
+ "train_samples_per_second": 2.088,
7
+ "train_steps_per_second": 0.261
8
+ }
chat_template.jinja ADDED
@@ -0,0 +1,47 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {{ bos_token }}
2
+ {%- if messages[0]['role'] == 'system' -%}
3
+ {%- if messages[0]['content'] is string -%}
4
+ {%- set first_user_prefix = messages[0]['content'] + '
5
+
6
+ ' -%}
7
+ {%- else -%}
8
+ {%- set first_user_prefix = messages[0]['content'][0]['text'] + '
9
+
10
+ ' -%}
11
+ {%- endif -%}
12
+ {%- set loop_messages = messages[1:] -%}
13
+ {%- else -%}
14
+ {%- set first_user_prefix = "" -%}
15
+ {%- set loop_messages = messages -%}
16
+ {%- endif -%}
17
+ {%- for message in loop_messages -%}
18
+ {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}
19
+ {{ raise_exception("Conversation roles must alternate user/assistant/user/assistant/...") }}
20
+ {%- endif -%}
21
+ {%- if (message['role'] == 'assistant') -%}
22
+ {%- set role = "model" -%}
23
+ {%- else -%}
24
+ {%- set role = message['role'] -%}
25
+ {%- endif -%}
26
+ {{ '<start_of_turn>' + role + '
27
+ ' + (first_user_prefix if loop.first else "") }}
28
+ {%- if message['content'] is string -%}
29
+ {{ message['content'] | trim }}
30
+ {%- elif message['content'] is iterable -%}
31
+ {%- for item in message['content'] -%}
32
+ {%- if item['type'] == 'image' -%}
33
+ {{ '<start_of_image>' }}
34
+ {%- elif item['type'] == 'text' -%}
35
+ {{ item['text'] | trim }}
36
+ {%- endif -%}
37
+ {%- endfor -%}
38
+ {%- else -%}
39
+ {{ raise_exception("Invalid content type") }}
40
+ {%- endif -%}
41
+ {{ '<end_of_turn>
42
+ ' }}
43
+ {%- endfor -%}
44
+ {%- if add_generation_prompt -%}
45
+ {{'<start_of_turn>model
46
+ '}}
47
+ {%- endif -%}
checkpoint-1000/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: google/gemma-3-4b-it
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.15.2
checkpoint-1000/adapter_config.json ADDED
@@ -0,0 +1,138 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "google/gemma-3-4b-it",
5
+ "bias": "none",
6
+ "corda_config": null,
7
+ "eva_config": null,
8
+ "exclude_modules": null,
9
+ "fan_in_fan_out": false,
10
+ "inference_mode": true,
11
+ "init_lora_weights": true,
12
+ "layer_replication": null,
13
+ "layers_pattern": null,
14
+ "layers_to_transform": null,
15
+ "loftq_config": {},
16
+ "lora_alpha": 16,
17
+ "lora_bias": false,
18
+ "lora_dropout": 0.0,
19
+ "megatron_config": null,
20
+ "megatron_core": "megatron.core",
21
+ "modules_to_save": null,
22
+ "peft_type": "LORA",
23
+ "r": 8,
24
+ "rank_pattern": {},
25
+ "revision": null,
26
+ "target_modules": [
27
+ "language_model.layers.13.self_attn.q_proj",
28
+ "language_model.layers.11.self_attn.k_proj",
29
+ "language_model.layers.7.self_attn.k_proj",
30
+ "language_model.layers.15.self_attn.v_proj",
31
+ "language_model.layers.15.self_attn.k_proj",
32
+ "language_model.layers.26.self_attn.v_proj",
33
+ "o_proj",
34
+ "language_model.layers.7.self_attn.v_proj",
35
+ "32.self_attn.k_proj",
36
+ "27.self_attn.q_proj",
37
+ "language_model.layers.14.self_attn.q_proj",
38
+ "language_model.layers.6.self_attn.q_proj",
39
+ "33.self_attn.q_proj",
40
+ "language_model.layers.13.self_attn.v_proj",
41
+ "language_model.layers.18.self_attn.q_proj",
42
+ "language_model.layers.11.self_attn.q_proj",
43
+ "28.self_attn.q_proj",
44
+ "language_model.layers.19.self_attn.q_proj",
45
+ "27.self_attn.v_proj",
46
+ "language_model.layers.24.self_attn.q_proj",
47
+ "language_model.layers.22.self_attn.k_proj",
48
+ "language_model.layers.25.self_attn.v_proj",
49
+ "language_model.layers.26.self_attn.q_proj",
50
+ "29.self_attn.k_proj",
51
+ "language_model.layers.24.self_attn.k_proj",
52
+ "language_model.layers.25.self_attn.q_proj",
53
+ "down_proj",
54
+ "language_model.layers.20.self_attn.q_proj",
55
+ "language_model.layers.10.self_attn.v_proj",
56
+ "30.self_attn.q_proj",
57
+ "33.self_attn.v_proj",
58
+ "language_model.layers.4.self_attn.q_proj",
59
+ "language_model.layers.18.self_attn.v_proj",
60
+ "31.self_attn.q_proj",
61
+ "33.self_attn.k_proj",
62
+ "language_model.layers.24.self_attn.v_proj",
63
+ "language_model.layers.23.self_attn.k_proj",
64
+ "language_model.layers.17.self_attn.k_proj",
65
+ "language_model.layers.0.self_attn.q_proj",
66
+ "language_model.layers.10.self_attn.q_proj",
67
+ "29.self_attn.v_proj",
68
+ "language_model.layers.1.self_attn.q_proj",
69
+ "30.self_attn.k_proj",
70
+ "language_model.layers.6.self_attn.k_proj",
71
+ "language_model.layers.1.self_attn.v_proj",
72
+ "28.self_attn.v_proj",
73
+ "language_model.layers.4.self_attn.v_proj",
74
+ "language_model.layers.0.self_attn.k_proj",
75
+ "30.self_attn.v_proj",
76
+ "28.self_attn.k_proj",
77
+ "language_model.layers.9.self_attn.v_proj",
78
+ "gate_proj",
79
+ "language_model.layers.4.self_attn.k_proj",
80
+ "language_model.layers.26.self_attn.k_proj",
81
+ "language_model.layers.3.self_attn.q_proj",
82
+ "language_model.layers.20.self_attn.v_proj",
83
+ "language_model.layers.5.self_attn.q_proj",
84
+ "language_model.layers.8.self_attn.q_proj",
85
+ "language_model.layers.16.self_attn.k_proj",
86
+ "language_model.layers.12.self_attn.k_proj",
87
+ "language_model.layers.2.self_attn.v_proj",
88
+ "language_model.layers.6.self_attn.v_proj",
89
+ "language_model.layers.12.self_attn.q_proj",
90
+ "language_model.layers.17.self_attn.v_proj",
91
+ "31.self_attn.v_proj",
92
+ "language_model.layers.16.self_attn.v_proj",
93
+ "language_model.layers.20.self_attn.k_proj",
94
+ "language_model.layers.12.self_attn.v_proj",
95
+ "language_model.layers.3.self_attn.k_proj",
96
+ "language_model.layers.8.self_attn.v_proj",
97
+ "language_model.layers.3.self_attn.v_proj",
98
+ "32.self_attn.v_proj",
99
+ "27.self_attn.k_proj",
100
+ "language_model.layers.5.self_attn.v_proj",
101
+ "language_model.layers.10.self_attn.k_proj",
102
+ "31.self_attn.k_proj",
103
+ "language_model.layers.16.self_attn.q_proj",
104
+ "language_model.layers.22.self_attn.v_proj",
105
+ "language_model.layers.9.self_attn.k_proj",
106
+ "language_model.layers.2.self_attn.q_proj",
107
+ "language_model.layers.19.self_attn.k_proj",
108
+ "language_model.layers.2.self_attn.k_proj",
109
+ "language_model.layers.23.self_attn.v_proj",
110
+ "language_model.layers.9.self_attn.q_proj",
111
+ "language_model.layers.14.self_attn.v_proj",
112
+ "language_model.layers.0.self_attn.v_proj",
113
+ "language_model.layers.21.self_attn.v_proj",
114
+ "language_model.layers.19.self_attn.v_proj",
115
+ "29.self_attn.q_proj",
116
+ "language_model.layers.15.self_attn.q_proj",
117
+ "language_model.layers.22.self_attn.q_proj",
118
+ "language_model.layers.21.self_attn.q_proj",
119
+ "language_model.layers.17.self_attn.q_proj",
120
+ "language_model.layers.11.self_attn.v_proj",
121
+ "language_model.layers.18.self_attn.k_proj",
122
+ "language_model.layers.25.self_attn.k_proj",
123
+ "language_model.layers.7.self_attn.q_proj",
124
+ "32.self_attn.q_proj",
125
+ "language_model.layers.23.self_attn.q_proj",
126
+ "language_model.layers.21.self_attn.k_proj",
127
+ "language_model.layers.5.self_attn.k_proj",
128
+ "language_model.layers.8.self_attn.k_proj",
129
+ "language_model.layers.13.self_attn.k_proj",
130
+ "up_proj",
131
+ "language_model.layers.1.self_attn.k_proj",
132
+ "language_model.layers.14.self_attn.k_proj"
133
+ ],
134
+ "task_type": "CAUSAL_LM",
135
+ "trainable_token_indices": null,
136
+ "use_dora": false,
137
+ "use_rslora": false
138
+ }
checkpoint-1000/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:35960e5670e7e7d0fb0baa078a3ad99a688d7db8d726146fbb640cc3ffa0c674
3
+ size 59675008
checkpoint-1000/added_tokens.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ {
2
+ "<image_soft_token>": 262144
3
+ }
checkpoint-1000/chat_template.jinja ADDED
@@ -0,0 +1,47 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {{ bos_token }}
2
+ {%- if messages[0]['role'] == 'system' -%}
3
+ {%- if messages[0]['content'] is string -%}
4
+ {%- set first_user_prefix = messages[0]['content'] + '
5
+
6
+ ' -%}
7
+ {%- else -%}
8
+ {%- set first_user_prefix = messages[0]['content'][0]['text'] + '
9
+
10
+ ' -%}
11
+ {%- endif -%}
12
+ {%- set loop_messages = messages[1:] -%}
13
+ {%- else -%}
14
+ {%- set first_user_prefix = "" -%}
15
+ {%- set loop_messages = messages -%}
16
+ {%- endif -%}
17
+ {%- for message in loop_messages -%}
18
+ {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}
19
+ {{ raise_exception("Conversation roles must alternate user/assistant/user/assistant/...") }}
20
+ {%- endif -%}
21
+ {%- if (message['role'] == 'assistant') -%}
22
+ {%- set role = "model" -%}
23
+ {%- else -%}
24
+ {%- set role = message['role'] -%}
25
+ {%- endif -%}
26
+ {{ '<start_of_turn>' + role + '
27
+ ' + (first_user_prefix if loop.first else "") }}
28
+ {%- if message['content'] is string -%}
29
+ {{ message['content'] | trim }}
30
+ {%- elif message['content'] is iterable -%}
31
+ {%- for item in message['content'] -%}
32
+ {%- if item['type'] == 'image' -%}
33
+ {{ '<start_of_image>' }}
34
+ {%- elif item['type'] == 'text' -%}
35
+ {{ item['text'] | trim }}
36
+ {%- endif -%}
37
+ {%- endfor -%}
38
+ {%- else -%}
39
+ {{ raise_exception("Invalid content type") }}
40
+ {%- endif -%}
41
+ {{ '<end_of_turn>
42
+ ' }}
43
+ {%- endfor -%}
44
+ {%- if add_generation_prompt -%}
45
+ {{'<start_of_turn>model
46
+ '}}
47
+ {%- endif -%}
checkpoint-1000/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:2e3214eb162a0475b56dbac451433d6170c5c24b68947fcd779cf08a8ee5b61f
3
+ size 119611063
checkpoint-1000/preprocessor_config.json ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "do_convert_rgb": null,
3
+ "do_normalize": true,
4
+ "do_pan_and_scan": null,
5
+ "do_rescale": true,
6
+ "do_resize": true,
7
+ "image_mean": [
8
+ 0.5,
9
+ 0.5,
10
+ 0.5
11
+ ],
12
+ "image_processor_type": "Gemma3ImageProcessor",
13
+ "image_seq_length": 256,
14
+ "image_std": [
15
+ 0.5,
16
+ 0.5,
17
+ 0.5
18
+ ],
19
+ "pan_and_scan_max_num_crops": null,
20
+ "pan_and_scan_min_crop_size": null,
21
+ "pan_and_scan_min_ratio_to_activate": null,
22
+ "processor_class": "Gemma3Processor",
23
+ "resample": 2,
24
+ "rescale_factor": 0.00392156862745098,
25
+ "size": {
26
+ "height": 896,
27
+ "width": 896
28
+ }
29
+ }
checkpoint-1000/processor_config.json ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ {
2
+ "image_seq_length": 256,
3
+ "processor_class": "Gemma3Processor"
4
+ }
checkpoint-1000/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:250560ab3d528161ab3659b120def6e4a9ab4b457e3399603bbcfa40db3efc90
3
+ size 14645
checkpoint-1000/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a7742f57d6748a994796e54556d7aa815c4953a13a94d3bf47d4e1c767c576e9
3
+ size 1465
checkpoint-1000/special_tokens_map.json ADDED
@@ -0,0 +1,33 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "boi_token": "<start_of_image>",
3
+ "bos_token": {
4
+ "content": "<bos>",
5
+ "lstrip": false,
6
+ "normalized": false,
7
+ "rstrip": false,
8
+ "single_word": false
9
+ },
10
+ "eoi_token": "<end_of_image>",
11
+ "eos_token": {
12
+ "content": "<end_of_turn>",
13
+ "lstrip": false,
14
+ "normalized": false,
15
+ "rstrip": false,
16
+ "single_word": false
17
+ },
18
+ "image_token": "<image_soft_token>",
19
+ "pad_token": {
20
+ "content": "<pad>",
21
+ "lstrip": false,
22
+ "normalized": false,
23
+ "rstrip": false,
24
+ "single_word": false
25
+ },
26
+ "unk_token": {
27
+ "content": "<unk>",
28
+ "lstrip": false,
29
+ "normalized": false,
30
+ "rstrip": false,
31
+ "single_word": false
32
+ }
33
+ }
checkpoint-1000/tokenizer.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:4667f2089529e8e7657cfb6d1c19910ae71ff5f28aa7ab2ff2763330affad795
3
+ size 33384568
checkpoint-1000/tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1299c11d7cf632ef3b4e11937501358ada021bbdf7c47638d13c0ee982f2e79c
3
+ size 4689074
checkpoint-1000/tokenizer_config.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-1000/trainer_state.json ADDED
@@ -0,0 +1,1434 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_global_step": null,
3
+ "best_metric": null,
4
+ "best_model_checkpoint": null,
5
+ "epoch": 0.557374764857521,
6
+ "eval_steps": 500,
7
+ "global_step": 1000,
8
+ "is_hyper_param_search": false,
9
+ "is_local_process_zero": true,
10
+ "is_world_process_zero": true,
11
+ "log_history": [
12
+ {
13
+ "epoch": 0.0027868738242876052,
14
+ "grad_norm": 3.519425630569458,
15
+ "learning_rate": 2.2222222222222225e-06,
16
+ "loss": 3.3173,
17
+ "step": 5
18
+ },
19
+ {
20
+ "epoch": 0.0055737476485752105,
21
+ "grad_norm": 3.5734193325042725,
22
+ "learning_rate": 5e-06,
23
+ "loss": 3.2709,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.008360621472862817,
28
+ "grad_norm": 3.3365390300750732,
29
+ "learning_rate": 7.777777777777777e-06,
30
+ "loss": 3.2597,
31
+ "step": 15
32
+ },
33
+ {
34
+ "epoch": 0.011147495297150421,
35
+ "grad_norm": 3.540066719055176,
36
+ "learning_rate": 1.0555555555555555e-05,
37
+ "loss": 3.3132,
38
+ "step": 20
39
+ },
40
+ {
41
+ "epoch": 0.013934369121438027,
42
+ "grad_norm": 3.4539105892181396,
43
+ "learning_rate": 1.3333333333333333e-05,
44
+ "loss": 3.174,
45
+ "step": 25
46
+ },
47
+ {
48
+ "epoch": 0.016721242945725634,
49
+ "grad_norm": 3.4685027599334717,
50
+ "learning_rate": 1.6111111111111115e-05,
51
+ "loss": 3.0624,
52
+ "step": 30
53
+ },
54
+ {
55
+ "epoch": 0.019508116770013236,
56
+ "grad_norm": 2.450899124145508,
57
+ "learning_rate": 1.888888888888889e-05,
58
+ "loss": 2.6596,
59
+ "step": 35
60
+ },
61
+ {
62
+ "epoch": 0.022294990594300842,
63
+ "grad_norm": 2.032400608062744,
64
+ "learning_rate": 2.1666666666666667e-05,
65
+ "loss": 2.3665,
66
+ "step": 40
67
+ },
68
+ {
69
+ "epoch": 0.025081864418588447,
70
+ "grad_norm": 1.888738989830017,
71
+ "learning_rate": 2.4444444444444445e-05,
72
+ "loss": 2.3122,
73
+ "step": 45
74
+ },
75
+ {
76
+ "epoch": 0.027868738242876053,
77
+ "grad_norm": 1.7904138565063477,
78
+ "learning_rate": 2.7222222222222223e-05,
79
+ "loss": 2.2123,
80
+ "step": 50
81
+ },
82
+ {
83
+ "epoch": 0.03065561206716366,
84
+ "grad_norm": 1.4838922023773193,
85
+ "learning_rate": 3e-05,
86
+ "loss": 1.9776,
87
+ "step": 55
88
+ },
89
+ {
90
+ "epoch": 0.03344248589145127,
91
+ "grad_norm": 1.3657710552215576,
92
+ "learning_rate": 3.277777777777778e-05,
93
+ "loss": 2.1255,
94
+ "step": 60
95
+ },
96
+ {
97
+ "epoch": 0.03622935971573887,
98
+ "grad_norm": 1.5868932008743286,
99
+ "learning_rate": 3.555555555555556e-05,
100
+ "loss": 2.002,
101
+ "step": 65
102
+ },
103
+ {
104
+ "epoch": 0.03901623354002647,
105
+ "grad_norm": 1.3804534673690796,
106
+ "learning_rate": 3.8333333333333334e-05,
107
+ "loss": 1.8644,
108
+ "step": 70
109
+ },
110
+ {
111
+ "epoch": 0.04180310736431408,
112
+ "grad_norm": 1.6571189165115356,
113
+ "learning_rate": 4.111111111111111e-05,
114
+ "loss": 1.9289,
115
+ "step": 75
116
+ },
117
+ {
118
+ "epoch": 0.044589981188601684,
119
+ "grad_norm": 1.3903523683547974,
120
+ "learning_rate": 4.388888888888889e-05,
121
+ "loss": 1.8229,
122
+ "step": 80
123
+ },
124
+ {
125
+ "epoch": 0.04737685501288929,
126
+ "grad_norm": 1.4426414966583252,
127
+ "learning_rate": 4.666666666666667e-05,
128
+ "loss": 1.9695,
129
+ "step": 85
130
+ },
131
+ {
132
+ "epoch": 0.050163728837176895,
133
+ "grad_norm": 1.5044183731079102,
134
+ "learning_rate": 4.9444444444444446e-05,
135
+ "loss": 1.8628,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 0.0529506026614645,
140
+ "grad_norm": 1.5124356746673584,
141
+ "learning_rate": 5.222222222222223e-05,
142
+ "loss": 1.8234,
143
+ "step": 95
144
+ },
145
+ {
146
+ "epoch": 0.055737476485752106,
147
+ "grad_norm": 1.5525212287902832,
148
+ "learning_rate": 5.500000000000001e-05,
149
+ "loss": 1.7394,
150
+ "step": 100
151
+ },
152
+ {
153
+ "epoch": 0.05852435031003971,
154
+ "grad_norm": 1.292240858078003,
155
+ "learning_rate": 5.7777777777777776e-05,
156
+ "loss": 1.7931,
157
+ "step": 105
158
+ },
159
+ {
160
+ "epoch": 0.06131122413432732,
161
+ "grad_norm": 1.619165062904358,
162
+ "learning_rate": 6.055555555555555e-05,
163
+ "loss": 1.867,
164
+ "step": 110
165
+ },
166
+ {
167
+ "epoch": 0.06409809795861493,
168
+ "grad_norm": 1.4694631099700928,
169
+ "learning_rate": 6.333333333333333e-05,
170
+ "loss": 1.759,
171
+ "step": 115
172
+ },
173
+ {
174
+ "epoch": 0.06688497178290254,
175
+ "grad_norm": 1.3863086700439453,
176
+ "learning_rate": 6.611111111111111e-05,
177
+ "loss": 1.7736,
178
+ "step": 120
179
+ },
180
+ {
181
+ "epoch": 0.06967184560719013,
182
+ "grad_norm": 1.4961035251617432,
183
+ "learning_rate": 6.88888888888889e-05,
184
+ "loss": 1.8549,
185
+ "step": 125
186
+ },
187
+ {
188
+ "epoch": 0.07245871943147773,
189
+ "grad_norm": 1.5141528844833374,
190
+ "learning_rate": 7.166666666666667e-05,
191
+ "loss": 1.8265,
192
+ "step": 130
193
+ },
194
+ {
195
+ "epoch": 0.07524559325576534,
196
+ "grad_norm": 1.3990612030029297,
197
+ "learning_rate": 7.444444444444444e-05,
198
+ "loss": 1.7902,
199
+ "step": 135
200
+ },
201
+ {
202
+ "epoch": 0.07803246708005294,
203
+ "grad_norm": 1.4681600332260132,
204
+ "learning_rate": 7.722222222222223e-05,
205
+ "loss": 1.7768,
206
+ "step": 140
207
+ },
208
+ {
209
+ "epoch": 0.08081934090434055,
210
+ "grad_norm": 1.3138507604599,
211
+ "learning_rate": 8e-05,
212
+ "loss": 1.8685,
213
+ "step": 145
214
+ },
215
+ {
216
+ "epoch": 0.08360621472862816,
217
+ "grad_norm": 1.3969348669052124,
218
+ "learning_rate": 8.277777777777778e-05,
219
+ "loss": 1.8157,
220
+ "step": 150
221
+ },
222
+ {
223
+ "epoch": 0.08639308855291576,
224
+ "grad_norm": 1.2288333177566528,
225
+ "learning_rate": 8.555555555555556e-05,
226
+ "loss": 1.7786,
227
+ "step": 155
228
+ },
229
+ {
230
+ "epoch": 0.08917996237720337,
231
+ "grad_norm": 1.3890010118484497,
232
+ "learning_rate": 8.833333333333333e-05,
233
+ "loss": 1.7432,
234
+ "step": 160
235
+ },
236
+ {
237
+ "epoch": 0.09196683620149097,
238
+ "grad_norm": 1.331598162651062,
239
+ "learning_rate": 9.111111111111112e-05,
240
+ "loss": 1.7276,
241
+ "step": 165
242
+ },
243
+ {
244
+ "epoch": 0.09475371002577858,
245
+ "grad_norm": 1.2631566524505615,
246
+ "learning_rate": 9.388888888888889e-05,
247
+ "loss": 1.7796,
248
+ "step": 170
249
+ },
250
+ {
251
+ "epoch": 0.09754058385006618,
252
+ "grad_norm": 1.257093906402588,
253
+ "learning_rate": 9.666666666666667e-05,
254
+ "loss": 1.7827,
255
+ "step": 175
256
+ },
257
+ {
258
+ "epoch": 0.10032745767435379,
259
+ "grad_norm": 1.3225001096725464,
260
+ "learning_rate": 9.944444444444446e-05,
261
+ "loss": 1.7974,
262
+ "step": 180
263
+ },
264
+ {
265
+ "epoch": 0.1031143314986414,
266
+ "grad_norm": 1.273942232131958,
267
+ "learning_rate": 9.999848639521432e-05,
268
+ "loss": 1.709,
269
+ "step": 185
270
+ },
271
+ {
272
+ "epoch": 0.105901205322929,
273
+ "grad_norm": 1.254530668258667,
274
+ "learning_rate": 9.999233753283091e-05,
275
+ "loss": 1.714,
276
+ "step": 190
277
+ },
278
+ {
279
+ "epoch": 0.1086880791472166,
280
+ "grad_norm": 1.4002060890197754,
281
+ "learning_rate": 9.998145939378577e-05,
282
+ "loss": 1.7172,
283
+ "step": 195
284
+ },
285
+ {
286
+ "epoch": 0.11147495297150421,
287
+ "grad_norm": 1.3674697875976562,
288
+ "learning_rate": 9.996585300715116e-05,
289
+ "loss": 1.7474,
290
+ "step": 200
291
+ },
292
+ {
293
+ "epoch": 0.11426182679579182,
294
+ "grad_norm": 1.1483808755874634,
295
+ "learning_rate": 9.994551984929175e-05,
296
+ "loss": 1.7234,
297
+ "step": 205
298
+ },
299
+ {
300
+ "epoch": 0.11704870062007942,
301
+ "grad_norm": 1.003041386604309,
302
+ "learning_rate": 9.992046184372492e-05,
303
+ "loss": 1.7372,
304
+ "step": 210
305
+ },
306
+ {
307
+ "epoch": 0.11983557444436703,
308
+ "grad_norm": 1.165946364402771,
309
+ "learning_rate": 9.989068136093873e-05,
310
+ "loss": 1.6743,
311
+ "step": 215
312
+ },
313
+ {
314
+ "epoch": 0.12262244826865464,
315
+ "grad_norm": 1.2353969812393188,
316
+ "learning_rate": 9.985618121816779e-05,
317
+ "loss": 1.7903,
318
+ "step": 220
319
+ },
320
+ {
321
+ "epoch": 0.12540932209294225,
322
+ "grad_norm": 1.2136731147766113,
323
+ "learning_rate": 9.981696467912664e-05,
324
+ "loss": 1.7156,
325
+ "step": 225
326
+ },
327
+ {
328
+ "epoch": 0.12819619591722986,
329
+ "grad_norm": 1.2277964353561401,
330
+ "learning_rate": 9.97730354537011e-05,
331
+ "loss": 1.7318,
332
+ "step": 230
333
+ },
334
+ {
335
+ "epoch": 0.13098306974151747,
336
+ "grad_norm": 1.1066367626190186,
337
+ "learning_rate": 9.972439769759722e-05,
338
+ "loss": 1.5974,
339
+ "step": 235
340
+ },
341
+ {
342
+ "epoch": 0.13376994356580507,
343
+ "grad_norm": 1.246705412864685,
344
+ "learning_rate": 9.967105601194823e-05,
345
+ "loss": 1.7995,
346
+ "step": 240
347
+ },
348
+ {
349
+ "epoch": 0.13655681739009268,
350
+ "grad_norm": 1.3154339790344238,
351
+ "learning_rate": 9.961301544287922e-05,
352
+ "loss": 1.6535,
353
+ "step": 245
354
+ },
355
+ {
356
+ "epoch": 0.13934369121438026,
357
+ "grad_norm": 1.2998573780059814,
358
+ "learning_rate": 9.955028148102979e-05,
359
+ "loss": 1.677,
360
+ "step": 250
361
+ },
362
+ {
363
+ "epoch": 0.14213056503866786,
364
+ "grad_norm": 1.2409193515777588,
365
+ "learning_rate": 9.948286006103466e-05,
366
+ "loss": 1.8138,
367
+ "step": 255
368
+ },
369
+ {
370
+ "epoch": 0.14491743886295547,
371
+ "grad_norm": 1.2084343433380127,
372
+ "learning_rate": 9.941075756096226e-05,
373
+ "loss": 1.7348,
374
+ "step": 260
375
+ },
376
+ {
377
+ "epoch": 0.14770431268724307,
378
+ "grad_norm": 1.2116494178771973,
379
+ "learning_rate": 9.933398080171123e-05,
380
+ "loss": 1.7194,
381
+ "step": 265
382
+ },
383
+ {
384
+ "epoch": 0.15049118651153068,
385
+ "grad_norm": 1.1804791688919067,
386
+ "learning_rate": 9.925253704636543e-05,
387
+ "loss": 1.6909,
388
+ "step": 270
389
+ },
390
+ {
391
+ "epoch": 0.15327806033581828,
392
+ "grad_norm": 1.1809178590774536,
393
+ "learning_rate": 9.916643399950656e-05,
394
+ "loss": 1.7101,
395
+ "step": 275
396
+ },
397
+ {
398
+ "epoch": 0.1560649341601059,
399
+ "grad_norm": 1.231031060218811,
400
+ "learning_rate": 9.907567980648549e-05,
401
+ "loss": 1.6824,
402
+ "step": 280
403
+ },
404
+ {
405
+ "epoch": 0.1588518079843935,
406
+ "grad_norm": 1.0977656841278076,
407
+ "learning_rate": 9.898028305265169e-05,
408
+ "loss": 1.7868,
409
+ "step": 285
410
+ },
411
+ {
412
+ "epoch": 0.1616386818086811,
413
+ "grad_norm": 1.1203359365463257,
414
+ "learning_rate": 9.888025276254096e-05,
415
+ "loss": 1.7527,
416
+ "step": 290
417
+ },
418
+ {
419
+ "epoch": 0.1644255556329687,
420
+ "grad_norm": 1.184502124786377,
421
+ "learning_rate": 9.877559839902184e-05,
422
+ "loss": 1.7041,
423
+ "step": 295
424
+ },
425
+ {
426
+ "epoch": 0.1672124294572563,
427
+ "grad_norm": 1.2224472761154175,
428
+ "learning_rate": 9.86663298624003e-05,
429
+ "loss": 1.6746,
430
+ "step": 300
431
+ },
432
+ {
433
+ "epoch": 0.16999930328154392,
434
+ "grad_norm": 1.1980866193771362,
435
+ "learning_rate": 9.855245748948326e-05,
436
+ "loss": 1.7623,
437
+ "step": 305
438
+ },
439
+ {
440
+ "epoch": 0.17278617710583152,
441
+ "grad_norm": 1.103948950767517,
442
+ "learning_rate": 9.843399205260068e-05,
443
+ "loss": 1.7375,
444
+ "step": 310
445
+ },
446
+ {
447
+ "epoch": 0.17557305093011913,
448
+ "grad_norm": 1.2248247861862183,
449
+ "learning_rate": 9.831094475858652e-05,
450
+ "loss": 1.7179,
451
+ "step": 315
452
+ },
453
+ {
454
+ "epoch": 0.17835992475440673,
455
+ "grad_norm": 1.140920877456665,
456
+ "learning_rate": 9.818332724771857e-05,
457
+ "loss": 1.7628,
458
+ "step": 320
459
+ },
460
+ {
461
+ "epoch": 0.18114679857869434,
462
+ "grad_norm": 1.2001911401748657,
463
+ "learning_rate": 9.805115159261726e-05,
464
+ "loss": 1.6517,
465
+ "step": 325
466
+ },
467
+ {
468
+ "epoch": 0.18393367240298195,
469
+ "grad_norm": 1.1155130863189697,
470
+ "learning_rate": 9.791443029710361e-05,
471
+ "loss": 1.6474,
472
+ "step": 330
473
+ },
474
+ {
475
+ "epoch": 0.18672054622726955,
476
+ "grad_norm": 1.2037473917007446,
477
+ "learning_rate": 9.777317629501636e-05,
478
+ "loss": 1.6658,
479
+ "step": 335
480
+ },
481
+ {
482
+ "epoch": 0.18950742005155716,
483
+ "grad_norm": 1.0747089385986328,
484
+ "learning_rate": 9.762740294898846e-05,
485
+ "loss": 1.6205,
486
+ "step": 340
487
+ },
488
+ {
489
+ "epoch": 0.19229429387584476,
490
+ "grad_norm": 1.1513704061508179,
491
+ "learning_rate": 9.747712404918286e-05,
492
+ "loss": 1.6043,
493
+ "step": 345
494
+ },
495
+ {
496
+ "epoch": 0.19508116770013237,
497
+ "grad_norm": 1.3088418245315552,
498
+ "learning_rate": 9.732235381198813e-05,
499
+ "loss": 1.7093,
500
+ "step": 350
501
+ },
502
+ {
503
+ "epoch": 0.19786804152441997,
504
+ "grad_norm": 1.1009858846664429,
505
+ "learning_rate": 9.716310687867342e-05,
506
+ "loss": 1.5643,
507
+ "step": 355
508
+ },
509
+ {
510
+ "epoch": 0.20065491534870758,
511
+ "grad_norm": 1.1726269721984863,
512
+ "learning_rate": 9.699939831400351e-05,
513
+ "loss": 1.7759,
514
+ "step": 360
515
+ },
516
+ {
517
+ "epoch": 0.20344178917299519,
518
+ "grad_norm": 1.1522917747497559,
519
+ "learning_rate": 9.683124360481364e-05,
520
+ "loss": 1.6986,
521
+ "step": 365
522
+ },
523
+ {
524
+ "epoch": 0.2062286629972828,
525
+ "grad_norm": 1.2712469100952148,
526
+ "learning_rate": 9.665865865854445e-05,
527
+ "loss": 1.6801,
528
+ "step": 370
529
+ },
530
+ {
531
+ "epoch": 0.2090155368215704,
532
+ "grad_norm": 1.1304699182510376,
533
+ "learning_rate": 9.648165980173712e-05,
534
+ "loss": 1.6799,
535
+ "step": 375
536
+ },
537
+ {
538
+ "epoch": 0.211802410645858,
539
+ "grad_norm": 1.1489053964614868,
540
+ "learning_rate": 9.630026377848892e-05,
541
+ "loss": 1.702,
542
+ "step": 380
543
+ },
544
+ {
545
+ "epoch": 0.2145892844701456,
546
+ "grad_norm": 1.1118578910827637,
547
+ "learning_rate": 9.611448774886924e-05,
548
+ "loss": 1.6753,
549
+ "step": 385
550
+ },
551
+ {
552
+ "epoch": 0.2173761582944332,
553
+ "grad_norm": 1.1929900646209717,
554
+ "learning_rate": 9.592434928729616e-05,
555
+ "loss": 1.7438,
556
+ "step": 390
557
+ },
558
+ {
559
+ "epoch": 0.22016303211872082,
560
+ "grad_norm": 1.194979190826416,
561
+ "learning_rate": 9.572986638087396e-05,
562
+ "loss": 1.7018,
563
+ "step": 395
564
+ },
565
+ {
566
+ "epoch": 0.22294990594300843,
567
+ "grad_norm": 1.1083358526229858,
568
+ "learning_rate": 9.553105742769154e-05,
569
+ "loss": 1.6582,
570
+ "step": 400
571
+ },
572
+ {
573
+ "epoch": 0.22573677976729603,
574
+ "grad_norm": 1.1435223817825317,
575
+ "learning_rate": 9.532794123508197e-05,
576
+ "loss": 1.5243,
577
+ "step": 405
578
+ },
579
+ {
580
+ "epoch": 0.22852365359158364,
581
+ "grad_norm": 1.1564743518829346,
582
+ "learning_rate": 9.512053701784329e-05,
583
+ "loss": 1.6948,
584
+ "step": 410
585
+ },
586
+ {
587
+ "epoch": 0.23131052741587124,
588
+ "grad_norm": 1.1165233850479126,
589
+ "learning_rate": 9.490886439642081e-05,
590
+ "loss": 1.6642,
591
+ "step": 415
592
+ },
593
+ {
594
+ "epoch": 0.23409740124015885,
595
+ "grad_norm": 1.1142499446868896,
596
+ "learning_rate": 9.469294339505098e-05,
597
+ "loss": 1.7122,
598
+ "step": 420
599
+ },
600
+ {
601
+ "epoch": 0.23688427506444645,
602
+ "grad_norm": 1.155530333518982,
603
+ "learning_rate": 9.447279443986716e-05,
604
+ "loss": 1.6334,
605
+ "step": 425
606
+ },
607
+ {
608
+ "epoch": 0.23967114888873406,
609
+ "grad_norm": 1.199251413345337,
610
+ "learning_rate": 9.424843835696724e-05,
611
+ "loss": 1.6815,
612
+ "step": 430
613
+ },
614
+ {
615
+ "epoch": 0.24245802271302166,
616
+ "grad_norm": 1.1987923383712769,
617
+ "learning_rate": 9.401989637044355e-05,
618
+ "loss": 1.6123,
619
+ "step": 435
620
+ },
621
+ {
622
+ "epoch": 0.24524489653730927,
623
+ "grad_norm": 1.060792326927185,
624
+ "learning_rate": 9.3787190100375e-05,
625
+ "loss": 1.6684,
626
+ "step": 440
627
+ },
628
+ {
629
+ "epoch": 0.24803177036159688,
630
+ "grad_norm": 1.098401665687561,
631
+ "learning_rate": 9.355034156078188e-05,
632
+ "loss": 1.6456,
633
+ "step": 445
634
+ },
635
+ {
636
+ "epoch": 0.2508186441858845,
637
+ "grad_norm": 1.0677911043167114,
638
+ "learning_rate": 9.330937315754329e-05,
639
+ "loss": 1.6516,
640
+ "step": 450
641
+ },
642
+ {
643
+ "epoch": 0.2536055180101721,
644
+ "grad_norm": 1.220309853553772,
645
+ "learning_rate": 9.306430768627753e-05,
646
+ "loss": 1.633,
647
+ "step": 455
648
+ },
649
+ {
650
+ "epoch": 0.2563923918344597,
651
+ "grad_norm": 1.2182236909866333,
652
+ "learning_rate": 9.281516833018571e-05,
653
+ "loss": 1.6457,
654
+ "step": 460
655
+ },
656
+ {
657
+ "epoch": 0.2591792656587473,
658
+ "grad_norm": 1.130843997001648,
659
+ "learning_rate": 9.256197865785854e-05,
660
+ "loss": 1.7424,
661
+ "step": 465
662
+ },
663
+ {
664
+ "epoch": 0.26196613948303493,
665
+ "grad_norm": 1.0312626361846924,
666
+ "learning_rate": 9.230476262104677e-05,
667
+ "loss": 1.6368,
668
+ "step": 470
669
+ },
670
+ {
671
+ "epoch": 0.26475301330732254,
672
+ "grad_norm": 1.0654799938201904,
673
+ "learning_rate": 9.204354455239539e-05,
674
+ "loss": 1.6771,
675
+ "step": 475
676
+ },
677
+ {
678
+ "epoch": 0.26753988713161014,
679
+ "grad_norm": 1.078287124633789,
680
+ "learning_rate": 9.177834916314165e-05,
681
+ "loss": 1.671,
682
+ "step": 480
683
+ },
684
+ {
685
+ "epoch": 0.27032676095589775,
686
+ "grad_norm": 1.067087173461914,
687
+ "learning_rate": 9.150920154077754e-05,
688
+ "loss": 1.6531,
689
+ "step": 485
690
+ },
691
+ {
692
+ "epoch": 0.27311363478018535,
693
+ "grad_norm": 1.1580300331115723,
694
+ "learning_rate": 9.123612714667634e-05,
695
+ "loss": 1.6917,
696
+ "step": 490
697
+ },
698
+ {
699
+ "epoch": 0.2759005086044729,
700
+ "grad_norm": 1.0481308698654175,
701
+ "learning_rate": 9.095915181368412e-05,
702
+ "loss": 1.7342,
703
+ "step": 495
704
+ },
705
+ {
706
+ "epoch": 0.2786873824287605,
707
+ "grad_norm": 1.150202751159668,
708
+ "learning_rate": 9.067830174367586e-05,
709
+ "loss": 1.7235,
710
+ "step": 500
711
+ },
712
+ {
713
+ "epoch": 0.2814742562530481,
714
+ "grad_norm": 1.046745777130127,
715
+ "learning_rate": 9.039360350507679e-05,
716
+ "loss": 1.6584,
717
+ "step": 505
718
+ },
719
+ {
720
+ "epoch": 0.2842611300773357,
721
+ "grad_norm": 1.1322135925292969,
722
+ "learning_rate": 9.010508403034898e-05,
723
+ "loss": 1.6262,
724
+ "step": 510
725
+ },
726
+ {
727
+ "epoch": 0.2870480039016233,
728
+ "grad_norm": 1.1856006383895874,
729
+ "learning_rate": 8.98127706134436e-05,
730
+ "loss": 1.6629,
731
+ "step": 515
732
+ },
733
+ {
734
+ "epoch": 0.28983487772591093,
735
+ "grad_norm": 1.1529713869094849,
736
+ "learning_rate": 8.951669090721881e-05,
737
+ "loss": 1.6786,
738
+ "step": 520
739
+ },
740
+ {
741
+ "epoch": 0.29262175155019854,
742
+ "grad_norm": 1.1861884593963623,
743
+ "learning_rate": 8.921687292082393e-05,
744
+ "loss": 1.5883,
745
+ "step": 525
746
+ },
747
+ {
748
+ "epoch": 0.29540862537448614,
749
+ "grad_norm": 1.0213477611541748,
750
+ "learning_rate": 8.891334501704962e-05,
751
+ "loss": 1.6554,
752
+ "step": 530
753
+ },
754
+ {
755
+ "epoch": 0.29819549919877375,
756
+ "grad_norm": 1.1557466983795166,
757
+ "learning_rate": 8.86061359096449e-05,
758
+ "loss": 1.6068,
759
+ "step": 535
760
+ },
761
+ {
762
+ "epoch": 0.30098237302306136,
763
+ "grad_norm": 1.1405634880065918,
764
+ "learning_rate": 8.829527466060072e-05,
765
+ "loss": 1.51,
766
+ "step": 540
767
+ },
768
+ {
769
+ "epoch": 0.30376924684734896,
770
+ "grad_norm": 1.0441310405731201,
771
+ "learning_rate": 8.798079067740077e-05,
772
+ "loss": 1.7514,
773
+ "step": 545
774
+ },
775
+ {
776
+ "epoch": 0.30655612067163657,
777
+ "grad_norm": 1.1396404504776,
778
+ "learning_rate": 8.766271371023948e-05,
779
+ "loss": 1.6459,
780
+ "step": 550
781
+ },
782
+ {
783
+ "epoch": 0.3093429944959242,
784
+ "grad_norm": 1.149436354637146,
785
+ "learning_rate": 8.73410738492077e-05,
786
+ "loss": 1.5749,
787
+ "step": 555
788
+ },
789
+ {
790
+ "epoch": 0.3121298683202118,
791
+ "grad_norm": 1.112534999847412,
792
+ "learning_rate": 8.701590152144612e-05,
793
+ "loss": 1.5966,
794
+ "step": 560
795
+ },
796
+ {
797
+ "epoch": 0.3149167421444994,
798
+ "grad_norm": 1.1014615297317505,
799
+ "learning_rate": 8.668722748826693e-05,
800
+ "loss": 1.6168,
801
+ "step": 565
802
+ },
803
+ {
804
+ "epoch": 0.317703615968787,
805
+ "grad_norm": 1.121466875076294,
806
+ "learning_rate": 8.635508284224371e-05,
807
+ "loss": 1.7761,
808
+ "step": 570
809
+ },
810
+ {
811
+ "epoch": 0.3204904897930746,
812
+ "grad_norm": 1.0950026512145996,
813
+ "learning_rate": 8.601949900427016e-05,
814
+ "loss": 1.5936,
815
+ "step": 575
816
+ },
817
+ {
818
+ "epoch": 0.3232773636173622,
819
+ "grad_norm": 1.1338622570037842,
820
+ "learning_rate": 8.568050772058762e-05,
821
+ "loss": 1.652,
822
+ "step": 580
823
+ },
824
+ {
825
+ "epoch": 0.3260642374416498,
826
+ "grad_norm": 1.1116234064102173,
827
+ "learning_rate": 8.533814105978191e-05,
828
+ "loss": 1.6174,
829
+ "step": 585
830
+ },
831
+ {
832
+ "epoch": 0.3288511112659374,
833
+ "grad_norm": 1.0834341049194336,
834
+ "learning_rate": 8.499243140974966e-05,
835
+ "loss": 1.6306,
836
+ "step": 590
837
+ },
838
+ {
839
+ "epoch": 0.331637985090225,
840
+ "grad_norm": 1.108328938484192,
841
+ "learning_rate": 8.464341147463431e-05,
842
+ "loss": 1.6114,
843
+ "step": 595
844
+ },
845
+ {
846
+ "epoch": 0.3344248589145126,
847
+ "grad_norm": 1.0812110900878906,
848
+ "learning_rate": 8.429111427173241e-05,
849
+ "loss": 1.5512,
850
+ "step": 600
851
+ },
852
+ {
853
+ "epoch": 0.33721173273880023,
854
+ "grad_norm": 1.0481332540512085,
855
+ "learning_rate": 8.393557312837018e-05,
856
+ "loss": 1.5912,
857
+ "step": 605
858
+ },
859
+ {
860
+ "epoch": 0.33999860656308784,
861
+ "grad_norm": 1.148055911064148,
862
+ "learning_rate": 8.357682167875062e-05,
863
+ "loss": 1.658,
864
+ "step": 610
865
+ },
866
+ {
867
+ "epoch": 0.34278548038737544,
868
+ "grad_norm": 1.1767280101776123,
869
+ "learning_rate": 8.321489386077192e-05,
870
+ "loss": 1.6388,
871
+ "step": 615
872
+ },
873
+ {
874
+ "epoch": 0.34557235421166305,
875
+ "grad_norm": 1.1227543354034424,
876
+ "learning_rate": 8.28498239128167e-05,
877
+ "loss": 1.6459,
878
+ "step": 620
879
+ },
880
+ {
881
+ "epoch": 0.34835922803595065,
882
+ "grad_norm": 1.0740199089050293,
883
+ "learning_rate": 8.248164637051321e-05,
884
+ "loss": 1.5866,
885
+ "step": 625
886
+ },
887
+ {
888
+ "epoch": 0.35114610186023826,
889
+ "grad_norm": 1.1090576648712158,
890
+ "learning_rate": 8.211039606346826e-05,
891
+ "loss": 1.6677,
892
+ "step": 630
893
+ },
894
+ {
895
+ "epoch": 0.35393297568452586,
896
+ "grad_norm": 1.0976228713989258,
897
+ "learning_rate": 8.173610811197226e-05,
898
+ "loss": 1.6334,
899
+ "step": 635
900
+ },
901
+ {
902
+ "epoch": 0.35671984950881347,
903
+ "grad_norm": 1.0739277601242065,
904
+ "learning_rate": 8.135881792367686e-05,
905
+ "loss": 1.6535,
906
+ "step": 640
907
+ },
908
+ {
909
+ "epoch": 0.3595067233331011,
910
+ "grad_norm": 1.1656917333602905,
911
+ "learning_rate": 8.097856119024545e-05,
912
+ "loss": 1.6987,
913
+ "step": 645
914
+ },
915
+ {
916
+ "epoch": 0.3622935971573887,
917
+ "grad_norm": 1.0792914628982544,
918
+ "learning_rate": 8.059537388397665e-05,
919
+ "loss": 1.6375,
920
+ "step": 650
921
+ },
922
+ {
923
+ "epoch": 0.3650804709816763,
924
+ "grad_norm": 1.0863053798675537,
925
+ "learning_rate": 8.020929225440137e-05,
926
+ "loss": 1.6412,
927
+ "step": 655
928
+ },
929
+ {
930
+ "epoch": 0.3678673448059639,
931
+ "grad_norm": 1.1123287677764893,
932
+ "learning_rate": 7.98203528248536e-05,
933
+ "loss": 1.6451,
934
+ "step": 660
935
+ },
936
+ {
937
+ "epoch": 0.3706542186302515,
938
+ "grad_norm": 1.2055385112762451,
939
+ "learning_rate": 7.942859238901528e-05,
940
+ "loss": 1.6863,
941
+ "step": 665
942
+ },
943
+ {
944
+ "epoch": 0.3734410924545391,
945
+ "grad_norm": 1.2174745798110962,
946
+ "learning_rate": 7.903404800743564e-05,
947
+ "loss": 1.689,
948
+ "step": 670
949
+ },
950
+ {
951
+ "epoch": 0.3762279662788267,
952
+ "grad_norm": 1.2502973079681396,
953
+ "learning_rate": 7.863675700402526e-05,
954
+ "loss": 1.5926,
955
+ "step": 675
956
+ },
957
+ {
958
+ "epoch": 0.3790148401031143,
959
+ "grad_norm": 1.1077969074249268,
960
+ "learning_rate": 7.823675696252524e-05,
961
+ "loss": 1.7216,
962
+ "step": 680
963
+ },
964
+ {
965
+ "epoch": 0.3818017139274019,
966
+ "grad_norm": 1.1325827836990356,
967
+ "learning_rate": 7.783408572295174e-05,
968
+ "loss": 1.6753,
969
+ "step": 685
970
+ },
971
+ {
972
+ "epoch": 0.3845885877516895,
973
+ "grad_norm": 1.1358144283294678,
974
+ "learning_rate": 7.742878137801639e-05,
975
+ "loss": 1.6223,
976
+ "step": 690
977
+ },
978
+ {
979
+ "epoch": 0.38737546157597713,
980
+ "grad_norm": 1.0800058841705322,
981
+ "learning_rate": 7.702088226952258e-05,
982
+ "loss": 1.5979,
983
+ "step": 695
984
+ },
985
+ {
986
+ "epoch": 0.39016233540026474,
987
+ "grad_norm": 1.1636357307434082,
988
+ "learning_rate": 7.661042698473853e-05,
989
+ "loss": 1.5658,
990
+ "step": 700
991
+ },
992
+ {
993
+ "epoch": 0.39294920922455234,
994
+ "grad_norm": 1.0852898359298706,
995
+ "learning_rate": 7.619745435274667e-05,
996
+ "loss": 1.5857,
997
+ "step": 705
998
+ },
999
+ {
1000
+ "epoch": 0.39573608304883995,
1001
+ "grad_norm": 1.1379157304763794,
1002
+ "learning_rate": 7.578200344077073e-05,
1003
+ "loss": 1.6424,
1004
+ "step": 710
1005
+ },
1006
+ {
1007
+ "epoch": 0.39852295687312755,
1008
+ "grad_norm": 1.154302716255188,
1009
+ "learning_rate": 7.536411355047964e-05,
1010
+ "loss": 1.6375,
1011
+ "step": 715
1012
+ },
1013
+ {
1014
+ "epoch": 0.40130983069741516,
1015
+ "grad_norm": 1.105772852897644,
1016
+ "learning_rate": 7.494382421426984e-05,
1017
+ "loss": 1.6838,
1018
+ "step": 720
1019
+ },
1020
+ {
1021
+ "epoch": 0.40409670452170277,
1022
+ "grad_norm": 1.0883747339248657,
1023
+ "learning_rate": 7.452117519152542e-05,
1024
+ "loss": 1.5693,
1025
+ "step": 725
1026
+ },
1027
+ {
1028
+ "epoch": 0.40688357834599037,
1029
+ "grad_norm": 1.2045941352844238,
1030
+ "learning_rate": 7.409620646485685e-05,
1031
+ "loss": 1.5833,
1032
+ "step": 730
1033
+ },
1034
+ {
1035
+ "epoch": 0.409670452170278,
1036
+ "grad_norm": 1.0725213289260864,
1037
+ "learning_rate": 7.36689582363187e-05,
1038
+ "loss": 1.6385,
1039
+ "step": 735
1040
+ },
1041
+ {
1042
+ "epoch": 0.4124573259945656,
1043
+ "grad_norm": 1.0789135694503784,
1044
+ "learning_rate": 7.323947092360649e-05,
1045
+ "loss": 1.5517,
1046
+ "step": 740
1047
+ },
1048
+ {
1049
+ "epoch": 0.4152441998188532,
1050
+ "grad_norm": 1.1857792139053345,
1051
+ "learning_rate": 7.280778515623314e-05,
1052
+ "loss": 1.6848,
1053
+ "step": 745
1054
+ },
1055
+ {
1056
+ "epoch": 0.4180310736431408,
1057
+ "grad_norm": 1.2202659845352173,
1058
+ "learning_rate": 7.237394177168548e-05,
1059
+ "loss": 1.6484,
1060
+ "step": 750
1061
+ },
1062
+ {
1063
+ "epoch": 0.4208179474674284,
1064
+ "grad_norm": 1.2478704452514648,
1065
+ "learning_rate": 7.193798181156095e-05,
1066
+ "loss": 1.6772,
1067
+ "step": 755
1068
+ },
1069
+ {
1070
+ "epoch": 0.423604821291716,
1071
+ "grad_norm": 1.097607970237732,
1072
+ "learning_rate": 7.149994651768514e-05,
1073
+ "loss": 1.5013,
1074
+ "step": 760
1075
+ },
1076
+ {
1077
+ "epoch": 0.4263916951160036,
1078
+ "grad_norm": 1.182106852531433,
1079
+ "learning_rate": 7.10598773282103e-05,
1080
+ "loss": 1.651,
1081
+ "step": 765
1082
+ },
1083
+ {
1084
+ "epoch": 0.4291785689402912,
1085
+ "grad_norm": 1.222577452659607,
1086
+ "learning_rate": 7.061781587369519e-05,
1087
+ "loss": 1.7011,
1088
+ "step": 770
1089
+ },
1090
+ {
1091
+ "epoch": 0.4319654427645788,
1092
+ "grad_norm": 1.122916579246521,
1093
+ "learning_rate": 7.017380397316695e-05,
1094
+ "loss": 1.5754,
1095
+ "step": 775
1096
+ },
1097
+ {
1098
+ "epoch": 0.4347523165888664,
1099
+ "grad_norm": 1.1001543998718262,
1100
+ "learning_rate": 6.972788363016497e-05,
1101
+ "loss": 1.5028,
1102
+ "step": 780
1103
+ },
1104
+ {
1105
+ "epoch": 0.43753919041315403,
1106
+ "grad_norm": 1.1715834140777588,
1107
+ "learning_rate": 6.92800970287674e-05,
1108
+ "loss": 1.606,
1109
+ "step": 785
1110
+ },
1111
+ {
1112
+ "epoch": 0.44032606423744164,
1113
+ "grad_norm": 1.0918763875961304,
1114
+ "learning_rate": 6.883048652960038e-05,
1115
+ "loss": 1.6172,
1116
+ "step": 790
1117
+ },
1118
+ {
1119
+ "epoch": 0.44311293806172924,
1120
+ "grad_norm": 1.08346426486969,
1121
+ "learning_rate": 6.837909466583095e-05,
1122
+ "loss": 1.6295,
1123
+ "step": 795
1124
+ },
1125
+ {
1126
+ "epoch": 0.44589981188601685,
1127
+ "grad_norm": 1.0573424100875854,
1128
+ "learning_rate": 6.792596413914324e-05,
1129
+ "loss": 1.4928,
1130
+ "step": 800
1131
+ },
1132
+ {
1133
+ "epoch": 0.44868668571030446,
1134
+ "grad_norm": 1.1216208934783936,
1135
+ "learning_rate": 6.747113781569892e-05,
1136
+ "loss": 1.6603,
1137
+ "step": 805
1138
+ },
1139
+ {
1140
+ "epoch": 0.45147355953459206,
1141
+ "grad_norm": 1.1971062421798706,
1142
+ "learning_rate": 6.701465872208216e-05,
1143
+ "loss": 1.6791,
1144
+ "step": 810
1145
+ },
1146
+ {
1147
+ "epoch": 0.45426043335887967,
1148
+ "grad_norm": 1.2086865901947021,
1149
+ "learning_rate": 6.655657004122916e-05,
1150
+ "loss": 1.6836,
1151
+ "step": 815
1152
+ },
1153
+ {
1154
+ "epoch": 0.4570473071831673,
1155
+ "grad_norm": 1.1712608337402344,
1156
+ "learning_rate": 6.60969151083432e-05,
1157
+ "loss": 1.607,
1158
+ "step": 820
1159
+ },
1160
+ {
1161
+ "epoch": 0.4598341810074549,
1162
+ "grad_norm": 1.1016820669174194,
1163
+ "learning_rate": 6.563573740679496e-05,
1164
+ "loss": 1.5877,
1165
+ "step": 825
1166
+ },
1167
+ {
1168
+ "epoch": 0.4626210548317425,
1169
+ "grad_norm": 1.150856375694275,
1170
+ "learning_rate": 6.517308056400917e-05,
1171
+ "loss": 1.6316,
1172
+ "step": 830
1173
+ },
1174
+ {
1175
+ "epoch": 0.4654079286560301,
1176
+ "grad_norm": 1.0900683403015137,
1177
+ "learning_rate": 6.470898834733731e-05,
1178
+ "loss": 1.599,
1179
+ "step": 835
1180
+ },
1181
+ {
1182
+ "epoch": 0.4681948024803177,
1183
+ "grad_norm": 1.0819321870803833,
1184
+ "learning_rate": 6.42435046599173e-05,
1185
+ "loss": 1.6005,
1186
+ "step": 840
1187
+ },
1188
+ {
1189
+ "epoch": 0.4709816763046053,
1190
+ "grad_norm": 1.203545093536377,
1191
+ "learning_rate": 6.377667353652022e-05,
1192
+ "loss": 1.6524,
1193
+ "step": 845
1194
+ },
1195
+ {
1196
+ "epoch": 0.4737685501288929,
1197
+ "grad_norm": 1.1249206066131592,
1198
+ "learning_rate": 6.330853913938466e-05,
1199
+ "loss": 1.5626,
1200
+ "step": 850
1201
+ },
1202
+ {
1203
+ "epoch": 0.4765554239531805,
1204
+ "grad_norm": 1.0982279777526855,
1205
+ "learning_rate": 6.283914575403888e-05,
1206
+ "loss": 1.6691,
1207
+ "step": 855
1208
+ },
1209
+ {
1210
+ "epoch": 0.4793422977774681,
1211
+ "grad_norm": 1.147631287574768,
1212
+ "learning_rate": 6.236853778511156e-05,
1213
+ "loss": 1.5998,
1214
+ "step": 860
1215
+ },
1216
+ {
1217
+ "epoch": 0.4821291716017557,
1218
+ "grad_norm": 1.21993088722229,
1219
+ "learning_rate": 6.189675975213094e-05,
1220
+ "loss": 1.6185,
1221
+ "step": 865
1222
+ },
1223
+ {
1224
+ "epoch": 0.48491604542604333,
1225
+ "grad_norm": 1.1485539674758911,
1226
+ "learning_rate": 6.142385628531342e-05,
1227
+ "loss": 1.6378,
1228
+ "step": 870
1229
+ },
1230
+ {
1231
+ "epoch": 0.48770291925033094,
1232
+ "grad_norm": 1.198562741279602,
1233
+ "learning_rate": 6.09498721213414e-05,
1234
+ "loss": 1.5865,
1235
+ "step": 875
1236
+ },
1237
+ {
1238
+ "epoch": 0.49048979307461854,
1239
+ "grad_norm": 1.1535992622375488,
1240
+ "learning_rate": 6.047485209913137e-05,
1241
+ "loss": 1.6891,
1242
+ "step": 880
1243
+ },
1244
+ {
1245
+ "epoch": 0.49327666689890615,
1246
+ "grad_norm": 1.0472792387008667,
1247
+ "learning_rate": 5.999884115559192e-05,
1248
+ "loss": 1.5864,
1249
+ "step": 885
1250
+ },
1251
+ {
1252
+ "epoch": 0.49606354072319375,
1253
+ "grad_norm": 1.0315347909927368,
1254
+ "learning_rate": 5.952188432137293e-05,
1255
+ "loss": 1.6236,
1256
+ "step": 890
1257
+ },
1258
+ {
1259
+ "epoch": 0.49885041454748136,
1260
+ "grad_norm": 0.9921161532402039,
1261
+ "learning_rate": 5.90440267166055e-05,
1262
+ "loss": 1.5496,
1263
+ "step": 895
1264
+ },
1265
+ {
1266
+ "epoch": 0.501637288371769,
1267
+ "grad_norm": 1.2529871463775635,
1268
+ "learning_rate": 5.8565313546633684e-05,
1269
+ "loss": 1.6162,
1270
+ "step": 900
1271
+ },
1272
+ {
1273
+ "epoch": 0.5044241621960566,
1274
+ "grad_norm": 1.0699065923690796,
1275
+ "learning_rate": 5.8085790097738025e-05,
1276
+ "loss": 1.6587,
1277
+ "step": 905
1278
+ },
1279
+ {
1280
+ "epoch": 0.5072110360203442,
1281
+ "grad_norm": 1.1715635061264038,
1282
+ "learning_rate": 5.7605501732851475e-05,
1283
+ "loss": 1.6715,
1284
+ "step": 910
1285
+ },
1286
+ {
1287
+ "epoch": 0.5099979098446318,
1288
+ "grad_norm": 1.0690383911132812,
1289
+ "learning_rate": 5.712449388726807e-05,
1290
+ "loss": 1.6623,
1291
+ "step": 915
1292
+ },
1293
+ {
1294
+ "epoch": 0.5127847836689194,
1295
+ "grad_norm": 1.1124520301818848,
1296
+ "learning_rate": 5.664281206434472e-05,
1297
+ "loss": 1.5542,
1298
+ "step": 920
1299
+ },
1300
+ {
1301
+ "epoch": 0.515571657493207,
1302
+ "grad_norm": 1.104681134223938,
1303
+ "learning_rate": 5.616050183119663e-05,
1304
+ "loss": 1.6639,
1305
+ "step": 925
1306
+ },
1307
+ {
1308
+ "epoch": 0.5183585313174947,
1309
+ "grad_norm": 1.0456318855285645,
1310
+ "learning_rate": 5.5677608814386616e-05,
1311
+ "loss": 1.4796,
1312
+ "step": 930
1313
+ },
1314
+ {
1315
+ "epoch": 0.5211454051417822,
1316
+ "grad_norm": 1.20793879032135,
1317
+ "learning_rate": 5.519417869560889e-05,
1318
+ "loss": 1.5986,
1319
+ "step": 935
1320
+ },
1321
+ {
1322
+ "epoch": 0.5239322789660699,
1323
+ "grad_norm": 1.176321029663086,
1324
+ "learning_rate": 5.471025720736747e-05,
1325
+ "loss": 1.6518,
1326
+ "step": 940
1327
+ },
1328
+ {
1329
+ "epoch": 0.5267191527903574,
1330
+ "grad_norm": 1.1180968284606934,
1331
+ "learning_rate": 5.422589012864996e-05,
1332
+ "loss": 1.6476,
1333
+ "step": 945
1334
+ },
1335
+ {
1336
+ "epoch": 0.5295060266146451,
1337
+ "grad_norm": 1.2163270711898804,
1338
+ "learning_rate": 5.3741123280596864e-05,
1339
+ "loss": 1.5863,
1340
+ "step": 950
1341
+ },
1342
+ {
1343
+ "epoch": 0.5322929004389326,
1344
+ "grad_norm": 1.1990182399749756,
1345
+ "learning_rate": 5.325600252216685e-05,
1346
+ "loss": 1.5955,
1347
+ "step": 955
1348
+ },
1349
+ {
1350
+ "epoch": 0.5350797742632203,
1351
+ "grad_norm": 1.1612755060195923,
1352
+ "learning_rate": 5.27705737457985e-05,
1353
+ "loss": 1.4864,
1354
+ "step": 960
1355
+ },
1356
+ {
1357
+ "epoch": 0.5378666480875078,
1358
+ "grad_norm": 1.162166953086853,
1359
+ "learning_rate": 5.228488287306896e-05,
1360
+ "loss": 1.5999,
1361
+ "step": 965
1362
+ },
1363
+ {
1364
+ "epoch": 0.5406535219117955,
1365
+ "grad_norm": 1.0329886674880981,
1366
+ "learning_rate": 5.179897585034963e-05,
1367
+ "loss": 1.6147,
1368
+ "step": 970
1369
+ },
1370
+ {
1371
+ "epoch": 0.543440395736083,
1372
+ "grad_norm": 1.1080880165100098,
1373
+ "learning_rate": 5.1312898644459776e-05,
1374
+ "loss": 1.5184,
1375
+ "step": 975
1376
+ },
1377
+ {
1378
+ "epoch": 0.5462272695603707,
1379
+ "grad_norm": 1.1879712343215942,
1380
+ "learning_rate": 5.0826697238317935e-05,
1381
+ "loss": 1.5972,
1382
+ "step": 980
1383
+ },
1384
+ {
1385
+ "epoch": 0.5490141433846583,
1386
+ "grad_norm": 1.1458197832107544,
1387
+ "learning_rate": 5.0340417626592016e-05,
1388
+ "loss": 1.6351,
1389
+ "step": 985
1390
+ },
1391
+ {
1392
+ "epoch": 0.5518010172089458,
1393
+ "grad_norm": 1.1673814058303833,
1394
+ "learning_rate": 4.9854105811348216e-05,
1395
+ "loss": 1.6542,
1396
+ "step": 990
1397
+ },
1398
+ {
1399
+ "epoch": 0.5545878910332335,
1400
+ "grad_norm": 1.288260579109192,
1401
+ "learning_rate": 4.936780779769913e-05,
1402
+ "loss": 1.6248,
1403
+ "step": 995
1404
+ },
1405
+ {
1406
+ "epoch": 0.557374764857521,
1407
+ "grad_norm": 1.1573694944381714,
1408
+ "learning_rate": 4.888156958945174e-05,
1409
+ "loss": 1.5842,
1410
+ "step": 1000
1411
+ }
1412
+ ],
1413
+ "logging_steps": 5,
1414
+ "max_steps": 1795,
1415
+ "num_input_tokens_seen": 0,
1416
+ "num_train_epochs": 1,
1417
+ "save_steps": 500,
1418
+ "stateful_callbacks": {
1419
+ "TrainerControl": {
1420
+ "args": {
1421
+ "should_epoch_stop": false,
1422
+ "should_evaluate": false,
1423
+ "should_log": false,
1424
+ "should_save": true,
1425
+ "should_training_stop": false
1426
+ },
1427
+ "attributes": {}
1428
+ }
1429
+ },
1430
+ "total_flos": 7.628487948387302e+16,
1431
+ "train_batch_size": 1,
1432
+ "trial_name": null,
1433
+ "trial_params": null
1434
+ }
checkpoint-1000/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e1aa320b63b839db302f62b6b9c4d585113c78963c721e06eb11dc1a03601f4f
3
+ size 6161
checkpoint-1500/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: google/gemma-3-4b-it
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.15.2
checkpoint-1500/adapter_config.json ADDED
@@ -0,0 +1,138 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "google/gemma-3-4b-it",
5
+ "bias": "none",
6
+ "corda_config": null,
7
+ "eva_config": null,
8
+ "exclude_modules": null,
9
+ "fan_in_fan_out": false,
10
+ "inference_mode": true,
11
+ "init_lora_weights": true,
12
+ "layer_replication": null,
13
+ "layers_pattern": null,
14
+ "layers_to_transform": null,
15
+ "loftq_config": {},
16
+ "lora_alpha": 16,
17
+ "lora_bias": false,
18
+ "lora_dropout": 0.0,
19
+ "megatron_config": null,
20
+ "megatron_core": "megatron.core",
21
+ "modules_to_save": null,
22
+ "peft_type": "LORA",
23
+ "r": 8,
24
+ "rank_pattern": {},
25
+ "revision": null,
26
+ "target_modules": [
27
+ "language_model.layers.13.self_attn.q_proj",
28
+ "language_model.layers.11.self_attn.k_proj",
29
+ "language_model.layers.7.self_attn.k_proj",
30
+ "language_model.layers.15.self_attn.v_proj",
31
+ "language_model.layers.15.self_attn.k_proj",
32
+ "language_model.layers.26.self_attn.v_proj",
33
+ "o_proj",
34
+ "language_model.layers.7.self_attn.v_proj",
35
+ "32.self_attn.k_proj",
36
+ "27.self_attn.q_proj",
37
+ "language_model.layers.14.self_attn.q_proj",
38
+ "language_model.layers.6.self_attn.q_proj",
39
+ "33.self_attn.q_proj",
40
+ "language_model.layers.13.self_attn.v_proj",
41
+ "language_model.layers.18.self_attn.q_proj",
42
+ "language_model.layers.11.self_attn.q_proj",
43
+ "28.self_attn.q_proj",
44
+ "language_model.layers.19.self_attn.q_proj",
45
+ "27.self_attn.v_proj",
46
+ "language_model.layers.24.self_attn.q_proj",
47
+ "language_model.layers.22.self_attn.k_proj",
48
+ "language_model.layers.25.self_attn.v_proj",
49
+ "language_model.layers.26.self_attn.q_proj",
50
+ "29.self_attn.k_proj",
51
+ "language_model.layers.24.self_attn.k_proj",
52
+ "language_model.layers.25.self_attn.q_proj",
53
+ "down_proj",
54
+ "language_model.layers.20.self_attn.q_proj",
55
+ "language_model.layers.10.self_attn.v_proj",
56
+ "30.self_attn.q_proj",
57
+ "33.self_attn.v_proj",
58
+ "language_model.layers.4.self_attn.q_proj",
59
+ "language_model.layers.18.self_attn.v_proj",
60
+ "31.self_attn.q_proj",
61
+ "33.self_attn.k_proj",
62
+ "language_model.layers.24.self_attn.v_proj",
63
+ "language_model.layers.23.self_attn.k_proj",
64
+ "language_model.layers.17.self_attn.k_proj",
65
+ "language_model.layers.0.self_attn.q_proj",
66
+ "language_model.layers.10.self_attn.q_proj",
67
+ "29.self_attn.v_proj",
68
+ "language_model.layers.1.self_attn.q_proj",
69
+ "30.self_attn.k_proj",
70
+ "language_model.layers.6.self_attn.k_proj",
71
+ "language_model.layers.1.self_attn.v_proj",
72
+ "28.self_attn.v_proj",
73
+ "language_model.layers.4.self_attn.v_proj",
74
+ "language_model.layers.0.self_attn.k_proj",
75
+ "30.self_attn.v_proj",
76
+ "28.self_attn.k_proj",
77
+ "language_model.layers.9.self_attn.v_proj",
78
+ "gate_proj",
79
+ "language_model.layers.4.self_attn.k_proj",
80
+ "language_model.layers.26.self_attn.k_proj",
81
+ "language_model.layers.3.self_attn.q_proj",
82
+ "language_model.layers.20.self_attn.v_proj",
83
+ "language_model.layers.5.self_attn.q_proj",
84
+ "language_model.layers.8.self_attn.q_proj",
85
+ "language_model.layers.16.self_attn.k_proj",
86
+ "language_model.layers.12.self_attn.k_proj",
87
+ "language_model.layers.2.self_attn.v_proj",
88
+ "language_model.layers.6.self_attn.v_proj",
89
+ "language_model.layers.12.self_attn.q_proj",
90
+ "language_model.layers.17.self_attn.v_proj",
91
+ "31.self_attn.v_proj",
92
+ "language_model.layers.16.self_attn.v_proj",
93
+ "language_model.layers.20.self_attn.k_proj",
94
+ "language_model.layers.12.self_attn.v_proj",
95
+ "language_model.layers.3.self_attn.k_proj",
96
+ "language_model.layers.8.self_attn.v_proj",
97
+ "language_model.layers.3.self_attn.v_proj",
98
+ "32.self_attn.v_proj",
99
+ "27.self_attn.k_proj",
100
+ "language_model.layers.5.self_attn.v_proj",
101
+ "language_model.layers.10.self_attn.k_proj",
102
+ "31.self_attn.k_proj",
103
+ "language_model.layers.16.self_attn.q_proj",
104
+ "language_model.layers.22.self_attn.v_proj",
105
+ "language_model.layers.9.self_attn.k_proj",
106
+ "language_model.layers.2.self_attn.q_proj",
107
+ "language_model.layers.19.self_attn.k_proj",
108
+ "language_model.layers.2.self_attn.k_proj",
109
+ "language_model.layers.23.self_attn.v_proj",
110
+ "language_model.layers.9.self_attn.q_proj",
111
+ "language_model.layers.14.self_attn.v_proj",
112
+ "language_model.layers.0.self_attn.v_proj",
113
+ "language_model.layers.21.self_attn.v_proj",
114
+ "language_model.layers.19.self_attn.v_proj",
115
+ "29.self_attn.q_proj",
116
+ "language_model.layers.15.self_attn.q_proj",
117
+ "language_model.layers.22.self_attn.q_proj",
118
+ "language_model.layers.21.self_attn.q_proj",
119
+ "language_model.layers.17.self_attn.q_proj",
120
+ "language_model.layers.11.self_attn.v_proj",
121
+ "language_model.layers.18.self_attn.k_proj",
122
+ "language_model.layers.25.self_attn.k_proj",
123
+ "language_model.layers.7.self_attn.q_proj",
124
+ "32.self_attn.q_proj",
125
+ "language_model.layers.23.self_attn.q_proj",
126
+ "language_model.layers.21.self_attn.k_proj",
127
+ "language_model.layers.5.self_attn.k_proj",
128
+ "language_model.layers.8.self_attn.k_proj",
129
+ "language_model.layers.13.self_attn.k_proj",
130
+ "up_proj",
131
+ "language_model.layers.1.self_attn.k_proj",
132
+ "language_model.layers.14.self_attn.k_proj"
133
+ ],
134
+ "task_type": "CAUSAL_LM",
135
+ "trainable_token_indices": null,
136
+ "use_dora": false,
137
+ "use_rslora": false
138
+ }
checkpoint-1500/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:fa04cccc21546d9da9dd989b422c9250b75c0ae68eb46ca5325b24f4040cf861
3
+ size 59675008
checkpoint-1500/added_tokens.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ {
2
+ "<image_soft_token>": 262144
3
+ }
checkpoint-1500/chat_template.jinja ADDED
@@ -0,0 +1,47 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {{ bos_token }}
2
+ {%- if messages[0]['role'] == 'system' -%}
3
+ {%- if messages[0]['content'] is string -%}
4
+ {%- set first_user_prefix = messages[0]['content'] + '
5
+
6
+ ' -%}
7
+ {%- else -%}
8
+ {%- set first_user_prefix = messages[0]['content'][0]['text'] + '
9
+
10
+ ' -%}
11
+ {%- endif -%}
12
+ {%- set loop_messages = messages[1:] -%}
13
+ {%- else -%}
14
+ {%- set first_user_prefix = "" -%}
15
+ {%- set loop_messages = messages -%}
16
+ {%- endif -%}
17
+ {%- for message in loop_messages -%}
18
+ {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}
19
+ {{ raise_exception("Conversation roles must alternate user/assistant/user/assistant/...") }}
20
+ {%- endif -%}
21
+ {%- if (message['role'] == 'assistant') -%}
22
+ {%- set role = "model" -%}
23
+ {%- else -%}
24
+ {%- set role = message['role'] -%}
25
+ {%- endif -%}
26
+ {{ '<start_of_turn>' + role + '
27
+ ' + (first_user_prefix if loop.first else "") }}
28
+ {%- if message['content'] is string -%}
29
+ {{ message['content'] | trim }}
30
+ {%- elif message['content'] is iterable -%}
31
+ {%- for item in message['content'] -%}
32
+ {%- if item['type'] == 'image' -%}
33
+ {{ '<start_of_image>' }}
34
+ {%- elif item['type'] == 'text' -%}
35
+ {{ item['text'] | trim }}
36
+ {%- endif -%}
37
+ {%- endfor -%}
38
+ {%- else -%}
39
+ {{ raise_exception("Invalid content type") }}
40
+ {%- endif -%}
41
+ {{ '<end_of_turn>
42
+ ' }}
43
+ {%- endfor -%}
44
+ {%- if add_generation_prompt -%}
45
+ {{'<start_of_turn>model
46
+ '}}
47
+ {%- endif -%}
checkpoint-1500/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c8cf34ed5cbe536b4afffbe579f79c153f809a76c392c3c3ae8629792d8afb1d
3
+ size 119611063
checkpoint-1500/preprocessor_config.json ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "do_convert_rgb": null,
3
+ "do_normalize": true,
4
+ "do_pan_and_scan": null,
5
+ "do_rescale": true,
6
+ "do_resize": true,
7
+ "image_mean": [
8
+ 0.5,
9
+ 0.5,
10
+ 0.5
11
+ ],
12
+ "image_processor_type": "Gemma3ImageProcessor",
13
+ "image_seq_length": 256,
14
+ "image_std": [
15
+ 0.5,
16
+ 0.5,
17
+ 0.5
18
+ ],
19
+ "pan_and_scan_max_num_crops": null,
20
+ "pan_and_scan_min_crop_size": null,
21
+ "pan_and_scan_min_ratio_to_activate": null,
22
+ "processor_class": "Gemma3Processor",
23
+ "resample": 2,
24
+ "rescale_factor": 0.00392156862745098,
25
+ "size": {
26
+ "height": 896,
27
+ "width": 896
28
+ }
29
+ }
checkpoint-1500/processor_config.json ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ {
2
+ "image_seq_length": 256,
3
+ "processor_class": "Gemma3Processor"
4
+ }
checkpoint-1500/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:250560ab3d528161ab3659b120def6e4a9ab4b457e3399603bbcfa40db3efc90
3
+ size 14645
checkpoint-1500/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:74ecf9f08b8ece20f8e38217288ba9577a3fcfff91bb28828bd121972f45e8e0
3
+ size 1465
checkpoint-1500/special_tokens_map.json ADDED
@@ -0,0 +1,33 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "boi_token": "<start_of_image>",
3
+ "bos_token": {
4
+ "content": "<bos>",
5
+ "lstrip": false,
6
+ "normalized": false,
7
+ "rstrip": false,
8
+ "single_word": false
9
+ },
10
+ "eoi_token": "<end_of_image>",
11
+ "eos_token": {
12
+ "content": "<end_of_turn>",
13
+ "lstrip": false,
14
+ "normalized": false,
15
+ "rstrip": false,
16
+ "single_word": false
17
+ },
18
+ "image_token": "<image_soft_token>",
19
+ "pad_token": {
20
+ "content": "<pad>",
21
+ "lstrip": false,
22
+ "normalized": false,
23
+ "rstrip": false,
24
+ "single_word": false
25
+ },
26
+ "unk_token": {
27
+ "content": "<unk>",
28
+ "lstrip": false,
29
+ "normalized": false,
30
+ "rstrip": false,
31
+ "single_word": false
32
+ }
33
+ }
checkpoint-1500/tokenizer.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:4667f2089529e8e7657cfb6d1c19910ae71ff5f28aa7ab2ff2763330affad795
3
+ size 33384568
checkpoint-1500/tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1299c11d7cf632ef3b4e11937501358ada021bbdf7c47638d13c0ee982f2e79c
3
+ size 4689074
checkpoint-1500/tokenizer_config.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-1500/trainer_state.json ADDED
@@ -0,0 +1,2134 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_global_step": null,
3
+ "best_metric": null,
4
+ "best_model_checkpoint": null,
5
+ "epoch": 0.8360621472862816,
6
+ "eval_steps": 500,
7
+ "global_step": 1500,
8
+ "is_hyper_param_search": false,
9
+ "is_local_process_zero": true,
10
+ "is_world_process_zero": true,
11
+ "log_history": [
12
+ {
13
+ "epoch": 0.0027868738242876052,
14
+ "grad_norm": 3.519425630569458,
15
+ "learning_rate": 2.2222222222222225e-06,
16
+ "loss": 3.3173,
17
+ "step": 5
18
+ },
19
+ {
20
+ "epoch": 0.0055737476485752105,
21
+ "grad_norm": 3.5734193325042725,
22
+ "learning_rate": 5e-06,
23
+ "loss": 3.2709,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.008360621472862817,
28
+ "grad_norm": 3.3365390300750732,
29
+ "learning_rate": 7.777777777777777e-06,
30
+ "loss": 3.2597,
31
+ "step": 15
32
+ },
33
+ {
34
+ "epoch": 0.011147495297150421,
35
+ "grad_norm": 3.540066719055176,
36
+ "learning_rate": 1.0555555555555555e-05,
37
+ "loss": 3.3132,
38
+ "step": 20
39
+ },
40
+ {
41
+ "epoch": 0.013934369121438027,
42
+ "grad_norm": 3.4539105892181396,
43
+ "learning_rate": 1.3333333333333333e-05,
44
+ "loss": 3.174,
45
+ "step": 25
46
+ },
47
+ {
48
+ "epoch": 0.016721242945725634,
49
+ "grad_norm": 3.4685027599334717,
50
+ "learning_rate": 1.6111111111111115e-05,
51
+ "loss": 3.0624,
52
+ "step": 30
53
+ },
54
+ {
55
+ "epoch": 0.019508116770013236,
56
+ "grad_norm": 2.450899124145508,
57
+ "learning_rate": 1.888888888888889e-05,
58
+ "loss": 2.6596,
59
+ "step": 35
60
+ },
61
+ {
62
+ "epoch": 0.022294990594300842,
63
+ "grad_norm": 2.032400608062744,
64
+ "learning_rate": 2.1666666666666667e-05,
65
+ "loss": 2.3665,
66
+ "step": 40
67
+ },
68
+ {
69
+ "epoch": 0.025081864418588447,
70
+ "grad_norm": 1.888738989830017,
71
+ "learning_rate": 2.4444444444444445e-05,
72
+ "loss": 2.3122,
73
+ "step": 45
74
+ },
75
+ {
76
+ "epoch": 0.027868738242876053,
77
+ "grad_norm": 1.7904138565063477,
78
+ "learning_rate": 2.7222222222222223e-05,
79
+ "loss": 2.2123,
80
+ "step": 50
81
+ },
82
+ {
83
+ "epoch": 0.03065561206716366,
84
+ "grad_norm": 1.4838922023773193,
85
+ "learning_rate": 3e-05,
86
+ "loss": 1.9776,
87
+ "step": 55
88
+ },
89
+ {
90
+ "epoch": 0.03344248589145127,
91
+ "grad_norm": 1.3657710552215576,
92
+ "learning_rate": 3.277777777777778e-05,
93
+ "loss": 2.1255,
94
+ "step": 60
95
+ },
96
+ {
97
+ "epoch": 0.03622935971573887,
98
+ "grad_norm": 1.5868932008743286,
99
+ "learning_rate": 3.555555555555556e-05,
100
+ "loss": 2.002,
101
+ "step": 65
102
+ },
103
+ {
104
+ "epoch": 0.03901623354002647,
105
+ "grad_norm": 1.3804534673690796,
106
+ "learning_rate": 3.8333333333333334e-05,
107
+ "loss": 1.8644,
108
+ "step": 70
109
+ },
110
+ {
111
+ "epoch": 0.04180310736431408,
112
+ "grad_norm": 1.6571189165115356,
113
+ "learning_rate": 4.111111111111111e-05,
114
+ "loss": 1.9289,
115
+ "step": 75
116
+ },
117
+ {
118
+ "epoch": 0.044589981188601684,
119
+ "grad_norm": 1.3903523683547974,
120
+ "learning_rate": 4.388888888888889e-05,
121
+ "loss": 1.8229,
122
+ "step": 80
123
+ },
124
+ {
125
+ "epoch": 0.04737685501288929,
126
+ "grad_norm": 1.4426414966583252,
127
+ "learning_rate": 4.666666666666667e-05,
128
+ "loss": 1.9695,
129
+ "step": 85
130
+ },
131
+ {
132
+ "epoch": 0.050163728837176895,
133
+ "grad_norm": 1.5044183731079102,
134
+ "learning_rate": 4.9444444444444446e-05,
135
+ "loss": 1.8628,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 0.0529506026614645,
140
+ "grad_norm": 1.5124356746673584,
141
+ "learning_rate": 5.222222222222223e-05,
142
+ "loss": 1.8234,
143
+ "step": 95
144
+ },
145
+ {
146
+ "epoch": 0.055737476485752106,
147
+ "grad_norm": 1.5525212287902832,
148
+ "learning_rate": 5.500000000000001e-05,
149
+ "loss": 1.7394,
150
+ "step": 100
151
+ },
152
+ {
153
+ "epoch": 0.05852435031003971,
154
+ "grad_norm": 1.292240858078003,
155
+ "learning_rate": 5.7777777777777776e-05,
156
+ "loss": 1.7931,
157
+ "step": 105
158
+ },
159
+ {
160
+ "epoch": 0.06131122413432732,
161
+ "grad_norm": 1.619165062904358,
162
+ "learning_rate": 6.055555555555555e-05,
163
+ "loss": 1.867,
164
+ "step": 110
165
+ },
166
+ {
167
+ "epoch": 0.06409809795861493,
168
+ "grad_norm": 1.4694631099700928,
169
+ "learning_rate": 6.333333333333333e-05,
170
+ "loss": 1.759,
171
+ "step": 115
172
+ },
173
+ {
174
+ "epoch": 0.06688497178290254,
175
+ "grad_norm": 1.3863086700439453,
176
+ "learning_rate": 6.611111111111111e-05,
177
+ "loss": 1.7736,
178
+ "step": 120
179
+ },
180
+ {
181
+ "epoch": 0.06967184560719013,
182
+ "grad_norm": 1.4961035251617432,
183
+ "learning_rate": 6.88888888888889e-05,
184
+ "loss": 1.8549,
185
+ "step": 125
186
+ },
187
+ {
188
+ "epoch": 0.07245871943147773,
189
+ "grad_norm": 1.5141528844833374,
190
+ "learning_rate": 7.166666666666667e-05,
191
+ "loss": 1.8265,
192
+ "step": 130
193
+ },
194
+ {
195
+ "epoch": 0.07524559325576534,
196
+ "grad_norm": 1.3990612030029297,
197
+ "learning_rate": 7.444444444444444e-05,
198
+ "loss": 1.7902,
199
+ "step": 135
200
+ },
201
+ {
202
+ "epoch": 0.07803246708005294,
203
+ "grad_norm": 1.4681600332260132,
204
+ "learning_rate": 7.722222222222223e-05,
205
+ "loss": 1.7768,
206
+ "step": 140
207
+ },
208
+ {
209
+ "epoch": 0.08081934090434055,
210
+ "grad_norm": 1.3138507604599,
211
+ "learning_rate": 8e-05,
212
+ "loss": 1.8685,
213
+ "step": 145
214
+ },
215
+ {
216
+ "epoch": 0.08360621472862816,
217
+ "grad_norm": 1.3969348669052124,
218
+ "learning_rate": 8.277777777777778e-05,
219
+ "loss": 1.8157,
220
+ "step": 150
221
+ },
222
+ {
223
+ "epoch": 0.08639308855291576,
224
+ "grad_norm": 1.2288333177566528,
225
+ "learning_rate": 8.555555555555556e-05,
226
+ "loss": 1.7786,
227
+ "step": 155
228
+ },
229
+ {
230
+ "epoch": 0.08917996237720337,
231
+ "grad_norm": 1.3890010118484497,
232
+ "learning_rate": 8.833333333333333e-05,
233
+ "loss": 1.7432,
234
+ "step": 160
235
+ },
236
+ {
237
+ "epoch": 0.09196683620149097,
238
+ "grad_norm": 1.331598162651062,
239
+ "learning_rate": 9.111111111111112e-05,
240
+ "loss": 1.7276,
241
+ "step": 165
242
+ },
243
+ {
244
+ "epoch": 0.09475371002577858,
245
+ "grad_norm": 1.2631566524505615,
246
+ "learning_rate": 9.388888888888889e-05,
247
+ "loss": 1.7796,
248
+ "step": 170
249
+ },
250
+ {
251
+ "epoch": 0.09754058385006618,
252
+ "grad_norm": 1.257093906402588,
253
+ "learning_rate": 9.666666666666667e-05,
254
+ "loss": 1.7827,
255
+ "step": 175
256
+ },
257
+ {
258
+ "epoch": 0.10032745767435379,
259
+ "grad_norm": 1.3225001096725464,
260
+ "learning_rate": 9.944444444444446e-05,
261
+ "loss": 1.7974,
262
+ "step": 180
263
+ },
264
+ {
265
+ "epoch": 0.1031143314986414,
266
+ "grad_norm": 1.273942232131958,
267
+ "learning_rate": 9.999848639521432e-05,
268
+ "loss": 1.709,
269
+ "step": 185
270
+ },
271
+ {
272
+ "epoch": 0.105901205322929,
273
+ "grad_norm": 1.254530668258667,
274
+ "learning_rate": 9.999233753283091e-05,
275
+ "loss": 1.714,
276
+ "step": 190
277
+ },
278
+ {
279
+ "epoch": 0.1086880791472166,
280
+ "grad_norm": 1.4002060890197754,
281
+ "learning_rate": 9.998145939378577e-05,
282
+ "loss": 1.7172,
283
+ "step": 195
284
+ },
285
+ {
286
+ "epoch": 0.11147495297150421,
287
+ "grad_norm": 1.3674697875976562,
288
+ "learning_rate": 9.996585300715116e-05,
289
+ "loss": 1.7474,
290
+ "step": 200
291
+ },
292
+ {
293
+ "epoch": 0.11426182679579182,
294
+ "grad_norm": 1.1483808755874634,
295
+ "learning_rate": 9.994551984929175e-05,
296
+ "loss": 1.7234,
297
+ "step": 205
298
+ },
299
+ {
300
+ "epoch": 0.11704870062007942,
301
+ "grad_norm": 1.003041386604309,
302
+ "learning_rate": 9.992046184372492e-05,
303
+ "loss": 1.7372,
304
+ "step": 210
305
+ },
306
+ {
307
+ "epoch": 0.11983557444436703,
308
+ "grad_norm": 1.165946364402771,
309
+ "learning_rate": 9.989068136093873e-05,
310
+ "loss": 1.6743,
311
+ "step": 215
312
+ },
313
+ {
314
+ "epoch": 0.12262244826865464,
315
+ "grad_norm": 1.2353969812393188,
316
+ "learning_rate": 9.985618121816779e-05,
317
+ "loss": 1.7903,
318
+ "step": 220
319
+ },
320
+ {
321
+ "epoch": 0.12540932209294225,
322
+ "grad_norm": 1.2136731147766113,
323
+ "learning_rate": 9.981696467912664e-05,
324
+ "loss": 1.7156,
325
+ "step": 225
326
+ },
327
+ {
328
+ "epoch": 0.12819619591722986,
329
+ "grad_norm": 1.2277964353561401,
330
+ "learning_rate": 9.97730354537011e-05,
331
+ "loss": 1.7318,
332
+ "step": 230
333
+ },
334
+ {
335
+ "epoch": 0.13098306974151747,
336
+ "grad_norm": 1.1066367626190186,
337
+ "learning_rate": 9.972439769759722e-05,
338
+ "loss": 1.5974,
339
+ "step": 235
340
+ },
341
+ {
342
+ "epoch": 0.13376994356580507,
343
+ "grad_norm": 1.246705412864685,
344
+ "learning_rate": 9.967105601194823e-05,
345
+ "loss": 1.7995,
346
+ "step": 240
347
+ },
348
+ {
349
+ "epoch": 0.13655681739009268,
350
+ "grad_norm": 1.3154339790344238,
351
+ "learning_rate": 9.961301544287922e-05,
352
+ "loss": 1.6535,
353
+ "step": 245
354
+ },
355
+ {
356
+ "epoch": 0.13934369121438026,
357
+ "grad_norm": 1.2998573780059814,
358
+ "learning_rate": 9.955028148102979e-05,
359
+ "loss": 1.677,
360
+ "step": 250
361
+ },
362
+ {
363
+ "epoch": 0.14213056503866786,
364
+ "grad_norm": 1.2409193515777588,
365
+ "learning_rate": 9.948286006103466e-05,
366
+ "loss": 1.8138,
367
+ "step": 255
368
+ },
369
+ {
370
+ "epoch": 0.14491743886295547,
371
+ "grad_norm": 1.2084343433380127,
372
+ "learning_rate": 9.941075756096226e-05,
373
+ "loss": 1.7348,
374
+ "step": 260
375
+ },
376
+ {
377
+ "epoch": 0.14770431268724307,
378
+ "grad_norm": 1.2116494178771973,
379
+ "learning_rate": 9.933398080171123e-05,
380
+ "loss": 1.7194,
381
+ "step": 265
382
+ },
383
+ {
384
+ "epoch": 0.15049118651153068,
385
+ "grad_norm": 1.1804791688919067,
386
+ "learning_rate": 9.925253704636543e-05,
387
+ "loss": 1.6909,
388
+ "step": 270
389
+ },
390
+ {
391
+ "epoch": 0.15327806033581828,
392
+ "grad_norm": 1.1809178590774536,
393
+ "learning_rate": 9.916643399950656e-05,
394
+ "loss": 1.7101,
395
+ "step": 275
396
+ },
397
+ {
398
+ "epoch": 0.1560649341601059,
399
+ "grad_norm": 1.231031060218811,
400
+ "learning_rate": 9.907567980648549e-05,
401
+ "loss": 1.6824,
402
+ "step": 280
403
+ },
404
+ {
405
+ "epoch": 0.1588518079843935,
406
+ "grad_norm": 1.0977656841278076,
407
+ "learning_rate": 9.898028305265169e-05,
408
+ "loss": 1.7868,
409
+ "step": 285
410
+ },
411
+ {
412
+ "epoch": 0.1616386818086811,
413
+ "grad_norm": 1.1203359365463257,
414
+ "learning_rate": 9.888025276254096e-05,
415
+ "loss": 1.7527,
416
+ "step": 290
417
+ },
418
+ {
419
+ "epoch": 0.1644255556329687,
420
+ "grad_norm": 1.184502124786377,
421
+ "learning_rate": 9.877559839902184e-05,
422
+ "loss": 1.7041,
423
+ "step": 295
424
+ },
425
+ {
426
+ "epoch": 0.1672124294572563,
427
+ "grad_norm": 1.2224472761154175,
428
+ "learning_rate": 9.86663298624003e-05,
429
+ "loss": 1.6746,
430
+ "step": 300
431
+ },
432
+ {
433
+ "epoch": 0.16999930328154392,
434
+ "grad_norm": 1.1980866193771362,
435
+ "learning_rate": 9.855245748948326e-05,
436
+ "loss": 1.7623,
437
+ "step": 305
438
+ },
439
+ {
440
+ "epoch": 0.17278617710583152,
441
+ "grad_norm": 1.103948950767517,
442
+ "learning_rate": 9.843399205260068e-05,
443
+ "loss": 1.7375,
444
+ "step": 310
445
+ },
446
+ {
447
+ "epoch": 0.17557305093011913,
448
+ "grad_norm": 1.2248247861862183,
449
+ "learning_rate": 9.831094475858652e-05,
450
+ "loss": 1.7179,
451
+ "step": 315
452
+ },
453
+ {
454
+ "epoch": 0.17835992475440673,
455
+ "grad_norm": 1.140920877456665,
456
+ "learning_rate": 9.818332724771857e-05,
457
+ "loss": 1.7628,
458
+ "step": 320
459
+ },
460
+ {
461
+ "epoch": 0.18114679857869434,
462
+ "grad_norm": 1.2001911401748657,
463
+ "learning_rate": 9.805115159261726e-05,
464
+ "loss": 1.6517,
465
+ "step": 325
466
+ },
467
+ {
468
+ "epoch": 0.18393367240298195,
469
+ "grad_norm": 1.1155130863189697,
470
+ "learning_rate": 9.791443029710361e-05,
471
+ "loss": 1.6474,
472
+ "step": 330
473
+ },
474
+ {
475
+ "epoch": 0.18672054622726955,
476
+ "grad_norm": 1.2037473917007446,
477
+ "learning_rate": 9.777317629501636e-05,
478
+ "loss": 1.6658,
479
+ "step": 335
480
+ },
481
+ {
482
+ "epoch": 0.18950742005155716,
483
+ "grad_norm": 1.0747089385986328,
484
+ "learning_rate": 9.762740294898846e-05,
485
+ "loss": 1.6205,
486
+ "step": 340
487
+ },
488
+ {
489
+ "epoch": 0.19229429387584476,
490
+ "grad_norm": 1.1513704061508179,
491
+ "learning_rate": 9.747712404918286e-05,
492
+ "loss": 1.6043,
493
+ "step": 345
494
+ },
495
+ {
496
+ "epoch": 0.19508116770013237,
497
+ "grad_norm": 1.3088418245315552,
498
+ "learning_rate": 9.732235381198813e-05,
499
+ "loss": 1.7093,
500
+ "step": 350
501
+ },
502
+ {
503
+ "epoch": 0.19786804152441997,
504
+ "grad_norm": 1.1009858846664429,
505
+ "learning_rate": 9.716310687867342e-05,
506
+ "loss": 1.5643,
507
+ "step": 355
508
+ },
509
+ {
510
+ "epoch": 0.20065491534870758,
511
+ "grad_norm": 1.1726269721984863,
512
+ "learning_rate": 9.699939831400351e-05,
513
+ "loss": 1.7759,
514
+ "step": 360
515
+ },
516
+ {
517
+ "epoch": 0.20344178917299519,
518
+ "grad_norm": 1.1522917747497559,
519
+ "learning_rate": 9.683124360481364e-05,
520
+ "loss": 1.6986,
521
+ "step": 365
522
+ },
523
+ {
524
+ "epoch": 0.2062286629972828,
525
+ "grad_norm": 1.2712469100952148,
526
+ "learning_rate": 9.665865865854445e-05,
527
+ "loss": 1.6801,
528
+ "step": 370
529
+ },
530
+ {
531
+ "epoch": 0.2090155368215704,
532
+ "grad_norm": 1.1304699182510376,
533
+ "learning_rate": 9.648165980173712e-05,
534
+ "loss": 1.6799,
535
+ "step": 375
536
+ },
537
+ {
538
+ "epoch": 0.211802410645858,
539
+ "grad_norm": 1.1489053964614868,
540
+ "learning_rate": 9.630026377848892e-05,
541
+ "loss": 1.702,
542
+ "step": 380
543
+ },
544
+ {
545
+ "epoch": 0.2145892844701456,
546
+ "grad_norm": 1.1118578910827637,
547
+ "learning_rate": 9.611448774886924e-05,
548
+ "loss": 1.6753,
549
+ "step": 385
550
+ },
551
+ {
552
+ "epoch": 0.2173761582944332,
553
+ "grad_norm": 1.1929900646209717,
554
+ "learning_rate": 9.592434928729616e-05,
555
+ "loss": 1.7438,
556
+ "step": 390
557
+ },
558
+ {
559
+ "epoch": 0.22016303211872082,
560
+ "grad_norm": 1.194979190826416,
561
+ "learning_rate": 9.572986638087396e-05,
562
+ "loss": 1.7018,
563
+ "step": 395
564
+ },
565
+ {
566
+ "epoch": 0.22294990594300843,
567
+ "grad_norm": 1.1083358526229858,
568
+ "learning_rate": 9.553105742769154e-05,
569
+ "loss": 1.6582,
570
+ "step": 400
571
+ },
572
+ {
573
+ "epoch": 0.22573677976729603,
574
+ "grad_norm": 1.1435223817825317,
575
+ "learning_rate": 9.532794123508197e-05,
576
+ "loss": 1.5243,
577
+ "step": 405
578
+ },
579
+ {
580
+ "epoch": 0.22852365359158364,
581
+ "grad_norm": 1.1564743518829346,
582
+ "learning_rate": 9.512053701784329e-05,
583
+ "loss": 1.6948,
584
+ "step": 410
585
+ },
586
+ {
587
+ "epoch": 0.23131052741587124,
588
+ "grad_norm": 1.1165233850479126,
589
+ "learning_rate": 9.490886439642081e-05,
590
+ "loss": 1.6642,
591
+ "step": 415
592
+ },
593
+ {
594
+ "epoch": 0.23409740124015885,
595
+ "grad_norm": 1.1142499446868896,
596
+ "learning_rate": 9.469294339505098e-05,
597
+ "loss": 1.7122,
598
+ "step": 420
599
+ },
600
+ {
601
+ "epoch": 0.23688427506444645,
602
+ "grad_norm": 1.155530333518982,
603
+ "learning_rate": 9.447279443986716e-05,
604
+ "loss": 1.6334,
605
+ "step": 425
606
+ },
607
+ {
608
+ "epoch": 0.23967114888873406,
609
+ "grad_norm": 1.199251413345337,
610
+ "learning_rate": 9.424843835696724e-05,
611
+ "loss": 1.6815,
612
+ "step": 430
613
+ },
614
+ {
615
+ "epoch": 0.24245802271302166,
616
+ "grad_norm": 1.1987923383712769,
617
+ "learning_rate": 9.401989637044355e-05,
618
+ "loss": 1.6123,
619
+ "step": 435
620
+ },
621
+ {
622
+ "epoch": 0.24524489653730927,
623
+ "grad_norm": 1.060792326927185,
624
+ "learning_rate": 9.3787190100375e-05,
625
+ "loss": 1.6684,
626
+ "step": 440
627
+ },
628
+ {
629
+ "epoch": 0.24803177036159688,
630
+ "grad_norm": 1.098401665687561,
631
+ "learning_rate": 9.355034156078188e-05,
632
+ "loss": 1.6456,
633
+ "step": 445
634
+ },
635
+ {
636
+ "epoch": 0.2508186441858845,
637
+ "grad_norm": 1.0677911043167114,
638
+ "learning_rate": 9.330937315754329e-05,
639
+ "loss": 1.6516,
640
+ "step": 450
641
+ },
642
+ {
643
+ "epoch": 0.2536055180101721,
644
+ "grad_norm": 1.220309853553772,
645
+ "learning_rate": 9.306430768627753e-05,
646
+ "loss": 1.633,
647
+ "step": 455
648
+ },
649
+ {
650
+ "epoch": 0.2563923918344597,
651
+ "grad_norm": 1.2182236909866333,
652
+ "learning_rate": 9.281516833018571e-05,
653
+ "loss": 1.6457,
654
+ "step": 460
655
+ },
656
+ {
657
+ "epoch": 0.2591792656587473,
658
+ "grad_norm": 1.130843997001648,
659
+ "learning_rate": 9.256197865785854e-05,
660
+ "loss": 1.7424,
661
+ "step": 465
662
+ },
663
+ {
664
+ "epoch": 0.26196613948303493,
665
+ "grad_norm": 1.0312626361846924,
666
+ "learning_rate": 9.230476262104677e-05,
667
+ "loss": 1.6368,
668
+ "step": 470
669
+ },
670
+ {
671
+ "epoch": 0.26475301330732254,
672
+ "grad_norm": 1.0654799938201904,
673
+ "learning_rate": 9.204354455239539e-05,
674
+ "loss": 1.6771,
675
+ "step": 475
676
+ },
677
+ {
678
+ "epoch": 0.26753988713161014,
679
+ "grad_norm": 1.078287124633789,
680
+ "learning_rate": 9.177834916314165e-05,
681
+ "loss": 1.671,
682
+ "step": 480
683
+ },
684
+ {
685
+ "epoch": 0.27032676095589775,
686
+ "grad_norm": 1.067087173461914,
687
+ "learning_rate": 9.150920154077754e-05,
688
+ "loss": 1.6531,
689
+ "step": 485
690
+ },
691
+ {
692
+ "epoch": 0.27311363478018535,
693
+ "grad_norm": 1.1580300331115723,
694
+ "learning_rate": 9.123612714667634e-05,
695
+ "loss": 1.6917,
696
+ "step": 490
697
+ },
698
+ {
699
+ "epoch": 0.2759005086044729,
700
+ "grad_norm": 1.0481308698654175,
701
+ "learning_rate": 9.095915181368412e-05,
702
+ "loss": 1.7342,
703
+ "step": 495
704
+ },
705
+ {
706
+ "epoch": 0.2786873824287605,
707
+ "grad_norm": 1.150202751159668,
708
+ "learning_rate": 9.067830174367586e-05,
709
+ "loss": 1.7235,
710
+ "step": 500
711
+ },
712
+ {
713
+ "epoch": 0.2814742562530481,
714
+ "grad_norm": 1.046745777130127,
715
+ "learning_rate": 9.039360350507679e-05,
716
+ "loss": 1.6584,
717
+ "step": 505
718
+ },
719
+ {
720
+ "epoch": 0.2842611300773357,
721
+ "grad_norm": 1.1322135925292969,
722
+ "learning_rate": 9.010508403034898e-05,
723
+ "loss": 1.6262,
724
+ "step": 510
725
+ },
726
+ {
727
+ "epoch": 0.2870480039016233,
728
+ "grad_norm": 1.1856006383895874,
729
+ "learning_rate": 8.98127706134436e-05,
730
+ "loss": 1.6629,
731
+ "step": 515
732
+ },
733
+ {
734
+ "epoch": 0.28983487772591093,
735
+ "grad_norm": 1.1529713869094849,
736
+ "learning_rate": 8.951669090721881e-05,
737
+ "loss": 1.6786,
738
+ "step": 520
739
+ },
740
+ {
741
+ "epoch": 0.29262175155019854,
742
+ "grad_norm": 1.1861884593963623,
743
+ "learning_rate": 8.921687292082393e-05,
744
+ "loss": 1.5883,
745
+ "step": 525
746
+ },
747
+ {
748
+ "epoch": 0.29540862537448614,
749
+ "grad_norm": 1.0213477611541748,
750
+ "learning_rate": 8.891334501704962e-05,
751
+ "loss": 1.6554,
752
+ "step": 530
753
+ },
754
+ {
755
+ "epoch": 0.29819549919877375,
756
+ "grad_norm": 1.1557466983795166,
757
+ "learning_rate": 8.86061359096449e-05,
758
+ "loss": 1.6068,
759
+ "step": 535
760
+ },
761
+ {
762
+ "epoch": 0.30098237302306136,
763
+ "grad_norm": 1.1405634880065918,
764
+ "learning_rate": 8.829527466060072e-05,
765
+ "loss": 1.51,
766
+ "step": 540
767
+ },
768
+ {
769
+ "epoch": 0.30376924684734896,
770
+ "grad_norm": 1.0441310405731201,
771
+ "learning_rate": 8.798079067740077e-05,
772
+ "loss": 1.7514,
773
+ "step": 545
774
+ },
775
+ {
776
+ "epoch": 0.30655612067163657,
777
+ "grad_norm": 1.1396404504776,
778
+ "learning_rate": 8.766271371023948e-05,
779
+ "loss": 1.6459,
780
+ "step": 550
781
+ },
782
+ {
783
+ "epoch": 0.3093429944959242,
784
+ "grad_norm": 1.149436354637146,
785
+ "learning_rate": 8.73410738492077e-05,
786
+ "loss": 1.5749,
787
+ "step": 555
788
+ },
789
+ {
790
+ "epoch": 0.3121298683202118,
791
+ "grad_norm": 1.112534999847412,
792
+ "learning_rate": 8.701590152144612e-05,
793
+ "loss": 1.5966,
794
+ "step": 560
795
+ },
796
+ {
797
+ "epoch": 0.3149167421444994,
798
+ "grad_norm": 1.1014615297317505,
799
+ "learning_rate": 8.668722748826693e-05,
800
+ "loss": 1.6168,
801
+ "step": 565
802
+ },
803
+ {
804
+ "epoch": 0.317703615968787,
805
+ "grad_norm": 1.121466875076294,
806
+ "learning_rate": 8.635508284224371e-05,
807
+ "loss": 1.7761,
808
+ "step": 570
809
+ },
810
+ {
811
+ "epoch": 0.3204904897930746,
812
+ "grad_norm": 1.0950026512145996,
813
+ "learning_rate": 8.601949900427016e-05,
814
+ "loss": 1.5936,
815
+ "step": 575
816
+ },
817
+ {
818
+ "epoch": 0.3232773636173622,
819
+ "grad_norm": 1.1338622570037842,
820
+ "learning_rate": 8.568050772058762e-05,
821
+ "loss": 1.652,
822
+ "step": 580
823
+ },
824
+ {
825
+ "epoch": 0.3260642374416498,
826
+ "grad_norm": 1.1116234064102173,
827
+ "learning_rate": 8.533814105978191e-05,
828
+ "loss": 1.6174,
829
+ "step": 585
830
+ },
831
+ {
832
+ "epoch": 0.3288511112659374,
833
+ "grad_norm": 1.0834341049194336,
834
+ "learning_rate": 8.499243140974966e-05,
835
+ "loss": 1.6306,
836
+ "step": 590
837
+ },
838
+ {
839
+ "epoch": 0.331637985090225,
840
+ "grad_norm": 1.108328938484192,
841
+ "learning_rate": 8.464341147463431e-05,
842
+ "loss": 1.6114,
843
+ "step": 595
844
+ },
845
+ {
846
+ "epoch": 0.3344248589145126,
847
+ "grad_norm": 1.0812110900878906,
848
+ "learning_rate": 8.429111427173241e-05,
849
+ "loss": 1.5512,
850
+ "step": 600
851
+ },
852
+ {
853
+ "epoch": 0.33721173273880023,
854
+ "grad_norm": 1.0481332540512085,
855
+ "learning_rate": 8.393557312837018e-05,
856
+ "loss": 1.5912,
857
+ "step": 605
858
+ },
859
+ {
860
+ "epoch": 0.33999860656308784,
861
+ "grad_norm": 1.148055911064148,
862
+ "learning_rate": 8.357682167875062e-05,
863
+ "loss": 1.658,
864
+ "step": 610
865
+ },
866
+ {
867
+ "epoch": 0.34278548038737544,
868
+ "grad_norm": 1.1767280101776123,
869
+ "learning_rate": 8.321489386077192e-05,
870
+ "loss": 1.6388,
871
+ "step": 615
872
+ },
873
+ {
874
+ "epoch": 0.34557235421166305,
875
+ "grad_norm": 1.1227543354034424,
876
+ "learning_rate": 8.28498239128167e-05,
877
+ "loss": 1.6459,
878
+ "step": 620
879
+ },
880
+ {
881
+ "epoch": 0.34835922803595065,
882
+ "grad_norm": 1.0740199089050293,
883
+ "learning_rate": 8.248164637051321e-05,
884
+ "loss": 1.5866,
885
+ "step": 625
886
+ },
887
+ {
888
+ "epoch": 0.35114610186023826,
889
+ "grad_norm": 1.1090576648712158,
890
+ "learning_rate": 8.211039606346826e-05,
891
+ "loss": 1.6677,
892
+ "step": 630
893
+ },
894
+ {
895
+ "epoch": 0.35393297568452586,
896
+ "grad_norm": 1.0976228713989258,
897
+ "learning_rate": 8.173610811197226e-05,
898
+ "loss": 1.6334,
899
+ "step": 635
900
+ },
901
+ {
902
+ "epoch": 0.35671984950881347,
903
+ "grad_norm": 1.0739277601242065,
904
+ "learning_rate": 8.135881792367686e-05,
905
+ "loss": 1.6535,
906
+ "step": 640
907
+ },
908
+ {
909
+ "epoch": 0.3595067233331011,
910
+ "grad_norm": 1.1656917333602905,
911
+ "learning_rate": 8.097856119024545e-05,
912
+ "loss": 1.6987,
913
+ "step": 645
914
+ },
915
+ {
916
+ "epoch": 0.3622935971573887,
917
+ "grad_norm": 1.0792914628982544,
918
+ "learning_rate": 8.059537388397665e-05,
919
+ "loss": 1.6375,
920
+ "step": 650
921
+ },
922
+ {
923
+ "epoch": 0.3650804709816763,
924
+ "grad_norm": 1.0863053798675537,
925
+ "learning_rate": 8.020929225440137e-05,
926
+ "loss": 1.6412,
927
+ "step": 655
928
+ },
929
+ {
930
+ "epoch": 0.3678673448059639,
931
+ "grad_norm": 1.1123287677764893,
932
+ "learning_rate": 7.98203528248536e-05,
933
+ "loss": 1.6451,
934
+ "step": 660
935
+ },
936
+ {
937
+ "epoch": 0.3706542186302515,
938
+ "grad_norm": 1.2055385112762451,
939
+ "learning_rate": 7.942859238901528e-05,
940
+ "loss": 1.6863,
941
+ "step": 665
942
+ },
943
+ {
944
+ "epoch": 0.3734410924545391,
945
+ "grad_norm": 1.2174745798110962,
946
+ "learning_rate": 7.903404800743564e-05,
947
+ "loss": 1.689,
948
+ "step": 670
949
+ },
950
+ {
951
+ "epoch": 0.3762279662788267,
952
+ "grad_norm": 1.2502973079681396,
953
+ "learning_rate": 7.863675700402526e-05,
954
+ "loss": 1.5926,
955
+ "step": 675
956
+ },
957
+ {
958
+ "epoch": 0.3790148401031143,
959
+ "grad_norm": 1.1077969074249268,
960
+ "learning_rate": 7.823675696252524e-05,
961
+ "loss": 1.7216,
962
+ "step": 680
963
+ },
964
+ {
965
+ "epoch": 0.3818017139274019,
966
+ "grad_norm": 1.1325827836990356,
967
+ "learning_rate": 7.783408572295174e-05,
968
+ "loss": 1.6753,
969
+ "step": 685
970
+ },
971
+ {
972
+ "epoch": 0.3845885877516895,
973
+ "grad_norm": 1.1358144283294678,
974
+ "learning_rate": 7.742878137801639e-05,
975
+ "loss": 1.6223,
976
+ "step": 690
977
+ },
978
+ {
979
+ "epoch": 0.38737546157597713,
980
+ "grad_norm": 1.0800058841705322,
981
+ "learning_rate": 7.702088226952258e-05,
982
+ "loss": 1.5979,
983
+ "step": 695
984
+ },
985
+ {
986
+ "epoch": 0.39016233540026474,
987
+ "grad_norm": 1.1636357307434082,
988
+ "learning_rate": 7.661042698473853e-05,
989
+ "loss": 1.5658,
990
+ "step": 700
991
+ },
992
+ {
993
+ "epoch": 0.39294920922455234,
994
+ "grad_norm": 1.0852898359298706,
995
+ "learning_rate": 7.619745435274667e-05,
996
+ "loss": 1.5857,
997
+ "step": 705
998
+ },
999
+ {
1000
+ "epoch": 0.39573608304883995,
1001
+ "grad_norm": 1.1379157304763794,
1002
+ "learning_rate": 7.578200344077073e-05,
1003
+ "loss": 1.6424,
1004
+ "step": 710
1005
+ },
1006
+ {
1007
+ "epoch": 0.39852295687312755,
1008
+ "grad_norm": 1.154302716255188,
1009
+ "learning_rate": 7.536411355047964e-05,
1010
+ "loss": 1.6375,
1011
+ "step": 715
1012
+ },
1013
+ {
1014
+ "epoch": 0.40130983069741516,
1015
+ "grad_norm": 1.105772852897644,
1016
+ "learning_rate": 7.494382421426984e-05,
1017
+ "loss": 1.6838,
1018
+ "step": 720
1019
+ },
1020
+ {
1021
+ "epoch": 0.40409670452170277,
1022
+ "grad_norm": 1.0883747339248657,
1023
+ "learning_rate": 7.452117519152542e-05,
1024
+ "loss": 1.5693,
1025
+ "step": 725
1026
+ },
1027
+ {
1028
+ "epoch": 0.40688357834599037,
1029
+ "grad_norm": 1.2045941352844238,
1030
+ "learning_rate": 7.409620646485685e-05,
1031
+ "loss": 1.5833,
1032
+ "step": 730
1033
+ },
1034
+ {
1035
+ "epoch": 0.409670452170278,
1036
+ "grad_norm": 1.0725213289260864,
1037
+ "learning_rate": 7.36689582363187e-05,
1038
+ "loss": 1.6385,
1039
+ "step": 735
1040
+ },
1041
+ {
1042
+ "epoch": 0.4124573259945656,
1043
+ "grad_norm": 1.0789135694503784,
1044
+ "learning_rate": 7.323947092360649e-05,
1045
+ "loss": 1.5517,
1046
+ "step": 740
1047
+ },
1048
+ {
1049
+ "epoch": 0.4152441998188532,
1050
+ "grad_norm": 1.1857792139053345,
1051
+ "learning_rate": 7.280778515623314e-05,
1052
+ "loss": 1.6848,
1053
+ "step": 745
1054
+ },
1055
+ {
1056
+ "epoch": 0.4180310736431408,
1057
+ "grad_norm": 1.2202659845352173,
1058
+ "learning_rate": 7.237394177168548e-05,
1059
+ "loss": 1.6484,
1060
+ "step": 750
1061
+ },
1062
+ {
1063
+ "epoch": 0.4208179474674284,
1064
+ "grad_norm": 1.2478704452514648,
1065
+ "learning_rate": 7.193798181156095e-05,
1066
+ "loss": 1.6772,
1067
+ "step": 755
1068
+ },
1069
+ {
1070
+ "epoch": 0.423604821291716,
1071
+ "grad_norm": 1.097607970237732,
1072
+ "learning_rate": 7.149994651768514e-05,
1073
+ "loss": 1.5013,
1074
+ "step": 760
1075
+ },
1076
+ {
1077
+ "epoch": 0.4263916951160036,
1078
+ "grad_norm": 1.182106852531433,
1079
+ "learning_rate": 7.10598773282103e-05,
1080
+ "loss": 1.651,
1081
+ "step": 765
1082
+ },
1083
+ {
1084
+ "epoch": 0.4291785689402912,
1085
+ "grad_norm": 1.222577452659607,
1086
+ "learning_rate": 7.061781587369519e-05,
1087
+ "loss": 1.7011,
1088
+ "step": 770
1089
+ },
1090
+ {
1091
+ "epoch": 0.4319654427645788,
1092
+ "grad_norm": 1.122916579246521,
1093
+ "learning_rate": 7.017380397316695e-05,
1094
+ "loss": 1.5754,
1095
+ "step": 775
1096
+ },
1097
+ {
1098
+ "epoch": 0.4347523165888664,
1099
+ "grad_norm": 1.1001543998718262,
1100
+ "learning_rate": 6.972788363016497e-05,
1101
+ "loss": 1.5028,
1102
+ "step": 780
1103
+ },
1104
+ {
1105
+ "epoch": 0.43753919041315403,
1106
+ "grad_norm": 1.1715834140777588,
1107
+ "learning_rate": 6.92800970287674e-05,
1108
+ "loss": 1.606,
1109
+ "step": 785
1110
+ },
1111
+ {
1112
+ "epoch": 0.44032606423744164,
1113
+ "grad_norm": 1.0918763875961304,
1114
+ "learning_rate": 6.883048652960038e-05,
1115
+ "loss": 1.6172,
1116
+ "step": 790
1117
+ },
1118
+ {
1119
+ "epoch": 0.44311293806172924,
1120
+ "grad_norm": 1.08346426486969,
1121
+ "learning_rate": 6.837909466583095e-05,
1122
+ "loss": 1.6295,
1123
+ "step": 795
1124
+ },
1125
+ {
1126
+ "epoch": 0.44589981188601685,
1127
+ "grad_norm": 1.0573424100875854,
1128
+ "learning_rate": 6.792596413914324e-05,
1129
+ "loss": 1.4928,
1130
+ "step": 800
1131
+ },
1132
+ {
1133
+ "epoch": 0.44868668571030446,
1134
+ "grad_norm": 1.1216208934783936,
1135
+ "learning_rate": 6.747113781569892e-05,
1136
+ "loss": 1.6603,
1137
+ "step": 805
1138
+ },
1139
+ {
1140
+ "epoch": 0.45147355953459206,
1141
+ "grad_norm": 1.1971062421798706,
1142
+ "learning_rate": 6.701465872208216e-05,
1143
+ "loss": 1.6791,
1144
+ "step": 810
1145
+ },
1146
+ {
1147
+ "epoch": 0.45426043335887967,
1148
+ "grad_norm": 1.2086865901947021,
1149
+ "learning_rate": 6.655657004122916e-05,
1150
+ "loss": 1.6836,
1151
+ "step": 815
1152
+ },
1153
+ {
1154
+ "epoch": 0.4570473071831673,
1155
+ "grad_norm": 1.1712608337402344,
1156
+ "learning_rate": 6.60969151083432e-05,
1157
+ "loss": 1.607,
1158
+ "step": 820
1159
+ },
1160
+ {
1161
+ "epoch": 0.4598341810074549,
1162
+ "grad_norm": 1.1016820669174194,
1163
+ "learning_rate": 6.563573740679496e-05,
1164
+ "loss": 1.5877,
1165
+ "step": 825
1166
+ },
1167
+ {
1168
+ "epoch": 0.4626210548317425,
1169
+ "grad_norm": 1.150856375694275,
1170
+ "learning_rate": 6.517308056400917e-05,
1171
+ "loss": 1.6316,
1172
+ "step": 830
1173
+ },
1174
+ {
1175
+ "epoch": 0.4654079286560301,
1176
+ "grad_norm": 1.0900683403015137,
1177
+ "learning_rate": 6.470898834733731e-05,
1178
+ "loss": 1.599,
1179
+ "step": 835
1180
+ },
1181
+ {
1182
+ "epoch": 0.4681948024803177,
1183
+ "grad_norm": 1.0819321870803833,
1184
+ "learning_rate": 6.42435046599173e-05,
1185
+ "loss": 1.6005,
1186
+ "step": 840
1187
+ },
1188
+ {
1189
+ "epoch": 0.4709816763046053,
1190
+ "grad_norm": 1.203545093536377,
1191
+ "learning_rate": 6.377667353652022e-05,
1192
+ "loss": 1.6524,
1193
+ "step": 845
1194
+ },
1195
+ {
1196
+ "epoch": 0.4737685501288929,
1197
+ "grad_norm": 1.1249206066131592,
1198
+ "learning_rate": 6.330853913938466e-05,
1199
+ "loss": 1.5626,
1200
+ "step": 850
1201
+ },
1202
+ {
1203
+ "epoch": 0.4765554239531805,
1204
+ "grad_norm": 1.0982279777526855,
1205
+ "learning_rate": 6.283914575403888e-05,
1206
+ "loss": 1.6691,
1207
+ "step": 855
1208
+ },
1209
+ {
1210
+ "epoch": 0.4793422977774681,
1211
+ "grad_norm": 1.147631287574768,
1212
+ "learning_rate": 6.236853778511156e-05,
1213
+ "loss": 1.5998,
1214
+ "step": 860
1215
+ },
1216
+ {
1217
+ "epoch": 0.4821291716017557,
1218
+ "grad_norm": 1.21993088722229,
1219
+ "learning_rate": 6.189675975213094e-05,
1220
+ "loss": 1.6185,
1221
+ "step": 865
1222
+ },
1223
+ {
1224
+ "epoch": 0.48491604542604333,
1225
+ "grad_norm": 1.1485539674758911,
1226
+ "learning_rate": 6.142385628531342e-05,
1227
+ "loss": 1.6378,
1228
+ "step": 870
1229
+ },
1230
+ {
1231
+ "epoch": 0.48770291925033094,
1232
+ "grad_norm": 1.198562741279602,
1233
+ "learning_rate": 6.09498721213414e-05,
1234
+ "loss": 1.5865,
1235
+ "step": 875
1236
+ },
1237
+ {
1238
+ "epoch": 0.49048979307461854,
1239
+ "grad_norm": 1.1535992622375488,
1240
+ "learning_rate": 6.047485209913137e-05,
1241
+ "loss": 1.6891,
1242
+ "step": 880
1243
+ },
1244
+ {
1245
+ "epoch": 0.49327666689890615,
1246
+ "grad_norm": 1.0472792387008667,
1247
+ "learning_rate": 5.999884115559192e-05,
1248
+ "loss": 1.5864,
1249
+ "step": 885
1250
+ },
1251
+ {
1252
+ "epoch": 0.49606354072319375,
1253
+ "grad_norm": 1.0315347909927368,
1254
+ "learning_rate": 5.952188432137293e-05,
1255
+ "loss": 1.6236,
1256
+ "step": 890
1257
+ },
1258
+ {
1259
+ "epoch": 0.49885041454748136,
1260
+ "grad_norm": 0.9921161532402039,
1261
+ "learning_rate": 5.90440267166055e-05,
1262
+ "loss": 1.5496,
1263
+ "step": 895
1264
+ },
1265
+ {
1266
+ "epoch": 0.501637288371769,
1267
+ "grad_norm": 1.2529871463775635,
1268
+ "learning_rate": 5.8565313546633684e-05,
1269
+ "loss": 1.6162,
1270
+ "step": 900
1271
+ },
1272
+ {
1273
+ "epoch": 0.5044241621960566,
1274
+ "grad_norm": 1.0699065923690796,
1275
+ "learning_rate": 5.8085790097738025e-05,
1276
+ "loss": 1.6587,
1277
+ "step": 905
1278
+ },
1279
+ {
1280
+ "epoch": 0.5072110360203442,
1281
+ "grad_norm": 1.1715635061264038,
1282
+ "learning_rate": 5.7605501732851475e-05,
1283
+ "loss": 1.6715,
1284
+ "step": 910
1285
+ },
1286
+ {
1287
+ "epoch": 0.5099979098446318,
1288
+ "grad_norm": 1.0690383911132812,
1289
+ "learning_rate": 5.712449388726807e-05,
1290
+ "loss": 1.6623,
1291
+ "step": 915
1292
+ },
1293
+ {
1294
+ "epoch": 0.5127847836689194,
1295
+ "grad_norm": 1.1124520301818848,
1296
+ "learning_rate": 5.664281206434472e-05,
1297
+ "loss": 1.5542,
1298
+ "step": 920
1299
+ },
1300
+ {
1301
+ "epoch": 0.515571657493207,
1302
+ "grad_norm": 1.104681134223938,
1303
+ "learning_rate": 5.616050183119663e-05,
1304
+ "loss": 1.6639,
1305
+ "step": 925
1306
+ },
1307
+ {
1308
+ "epoch": 0.5183585313174947,
1309
+ "grad_norm": 1.0456318855285645,
1310
+ "learning_rate": 5.5677608814386616e-05,
1311
+ "loss": 1.4796,
1312
+ "step": 930
1313
+ },
1314
+ {
1315
+ "epoch": 0.5211454051417822,
1316
+ "grad_norm": 1.20793879032135,
1317
+ "learning_rate": 5.519417869560889e-05,
1318
+ "loss": 1.5986,
1319
+ "step": 935
1320
+ },
1321
+ {
1322
+ "epoch": 0.5239322789660699,
1323
+ "grad_norm": 1.176321029663086,
1324
+ "learning_rate": 5.471025720736747e-05,
1325
+ "loss": 1.6518,
1326
+ "step": 940
1327
+ },
1328
+ {
1329
+ "epoch": 0.5267191527903574,
1330
+ "grad_norm": 1.1180968284606934,
1331
+ "learning_rate": 5.422589012864996e-05,
1332
+ "loss": 1.6476,
1333
+ "step": 945
1334
+ },
1335
+ {
1336
+ "epoch": 0.5295060266146451,
1337
+ "grad_norm": 1.2163270711898804,
1338
+ "learning_rate": 5.3741123280596864e-05,
1339
+ "loss": 1.5863,
1340
+ "step": 950
1341
+ },
1342
+ {
1343
+ "epoch": 0.5322929004389326,
1344
+ "grad_norm": 1.1990182399749756,
1345
+ "learning_rate": 5.325600252216685e-05,
1346
+ "loss": 1.5955,
1347
+ "step": 955
1348
+ },
1349
+ {
1350
+ "epoch": 0.5350797742632203,
1351
+ "grad_norm": 1.1612755060195923,
1352
+ "learning_rate": 5.27705737457985e-05,
1353
+ "loss": 1.4864,
1354
+ "step": 960
1355
+ },
1356
+ {
1357
+ "epoch": 0.5378666480875078,
1358
+ "grad_norm": 1.162166953086853,
1359
+ "learning_rate": 5.228488287306896e-05,
1360
+ "loss": 1.5999,
1361
+ "step": 965
1362
+ },
1363
+ {
1364
+ "epoch": 0.5406535219117955,
1365
+ "grad_norm": 1.0329886674880981,
1366
+ "learning_rate": 5.179897585034963e-05,
1367
+ "loss": 1.6147,
1368
+ "step": 970
1369
+ },
1370
+ {
1371
+ "epoch": 0.543440395736083,
1372
+ "grad_norm": 1.1080880165100098,
1373
+ "learning_rate": 5.1312898644459776e-05,
1374
+ "loss": 1.5184,
1375
+ "step": 975
1376
+ },
1377
+ {
1378
+ "epoch": 0.5462272695603707,
1379
+ "grad_norm": 1.1879712343215942,
1380
+ "learning_rate": 5.0826697238317935e-05,
1381
+ "loss": 1.5972,
1382
+ "step": 980
1383
+ },
1384
+ {
1385
+ "epoch": 0.5490141433846583,
1386
+ "grad_norm": 1.1458197832107544,
1387
+ "learning_rate": 5.0340417626592016e-05,
1388
+ "loss": 1.6351,
1389
+ "step": 985
1390
+ },
1391
+ {
1392
+ "epoch": 0.5518010172089458,
1393
+ "grad_norm": 1.1673814058303833,
1394
+ "learning_rate": 4.9854105811348216e-05,
1395
+ "loss": 1.6542,
1396
+ "step": 990
1397
+ },
1398
+ {
1399
+ "epoch": 0.5545878910332335,
1400
+ "grad_norm": 1.288260579109192,
1401
+ "learning_rate": 4.936780779769913e-05,
1402
+ "loss": 1.6248,
1403
+ "step": 995
1404
+ },
1405
+ {
1406
+ "epoch": 0.557374764857521,
1407
+ "grad_norm": 1.1573694944381714,
1408
+ "learning_rate": 4.888156958945174e-05,
1409
+ "loss": 1.5842,
1410
+ "step": 1000
1411
+ },
1412
+ {
1413
+ "epoch": 0.5601616386818087,
1414
+ "grad_norm": 1.1595826148986816,
1415
+ "learning_rate": 4.839543718475543e-05,
1416
+ "loss": 1.5927,
1417
+ "step": 1005
1418
+ },
1419
+ {
1420
+ "epoch": 0.5629485125060962,
1421
+ "grad_norm": 1.152223825454712,
1422
+ "learning_rate": 4.790945657175061e-05,
1423
+ "loss": 1.5852,
1424
+ "step": 1010
1425
+ },
1426
+ {
1427
+ "epoch": 0.5657353863303839,
1428
+ "grad_norm": 1.248939037322998,
1429
+ "learning_rate": 4.742367372421811e-05,
1430
+ "loss": 1.6421,
1431
+ "step": 1015
1432
+ },
1433
+ {
1434
+ "epoch": 0.5685222601546714,
1435
+ "grad_norm": 1.2727152109146118,
1436
+ "learning_rate": 4.69381345972302e-05,
1437
+ "loss": 1.5424,
1438
+ "step": 1020
1439
+ },
1440
+ {
1441
+ "epoch": 0.5713091339789591,
1442
+ "grad_norm": 1.098766565322876,
1443
+ "learning_rate": 4.6452885122803205e-05,
1444
+ "loss": 1.5401,
1445
+ "step": 1025
1446
+ },
1447
+ {
1448
+ "epoch": 0.5740960078032467,
1449
+ "grad_norm": 1.0859525203704834,
1450
+ "learning_rate": 4.5967971205552194e-05,
1451
+ "loss": 1.6034,
1452
+ "step": 1030
1453
+ },
1454
+ {
1455
+ "epoch": 0.5768828816275343,
1456
+ "grad_norm": 1.1281769275665283,
1457
+ "learning_rate": 4.548343871834864e-05,
1458
+ "loss": 1.5912,
1459
+ "step": 1035
1460
+ },
1461
+ {
1462
+ "epoch": 0.5796697554518219,
1463
+ "grad_norm": 1.140081524848938,
1464
+ "learning_rate": 4.499933349798067e-05,
1465
+ "loss": 1.6444,
1466
+ "step": 1040
1467
+ },
1468
+ {
1469
+ "epoch": 0.5824566292761095,
1470
+ "grad_norm": 1.1529605388641357,
1471
+ "learning_rate": 4.451570134081694e-05,
1472
+ "loss": 1.6978,
1473
+ "step": 1045
1474
+ },
1475
+ {
1476
+ "epoch": 0.5852435031003971,
1477
+ "grad_norm": 1.046574592590332,
1478
+ "learning_rate": 4.403258799847433e-05,
1479
+ "loss": 1.5525,
1480
+ "step": 1050
1481
+ },
1482
+ {
1483
+ "epoch": 0.5880303769246847,
1484
+ "grad_norm": 1.237820029258728,
1485
+ "learning_rate": 4.3550039173489845e-05,
1486
+ "loss": 1.5835,
1487
+ "step": 1055
1488
+ },
1489
+ {
1490
+ "epoch": 0.5908172507489723,
1491
+ "grad_norm": 1.169889211654663,
1492
+ "learning_rate": 4.306810051499708e-05,
1493
+ "loss": 1.5218,
1494
+ "step": 1060
1495
+ },
1496
+ {
1497
+ "epoch": 0.59360412457326,
1498
+ "grad_norm": 1.2477936744689941,
1499
+ "learning_rate": 4.2586817614407895e-05,
1500
+ "loss": 1.5948,
1501
+ "step": 1065
1502
+ },
1503
+ {
1504
+ "epoch": 0.5963909983975475,
1505
+ "grad_norm": 0.9886555671691895,
1506
+ "learning_rate": 4.210623600109946e-05,
1507
+ "loss": 1.4564,
1508
+ "step": 1070
1509
+ },
1510
+ {
1511
+ "epoch": 0.5991778722218352,
1512
+ "grad_norm": 1.1212278604507446,
1513
+ "learning_rate": 4.162640113810706e-05,
1514
+ "loss": 1.6267,
1515
+ "step": 1075
1516
+ },
1517
+ {
1518
+ "epoch": 0.6019647460461227,
1519
+ "grad_norm": 1.1575827598571777,
1520
+ "learning_rate": 4.114735841782347e-05,
1521
+ "loss": 1.6716,
1522
+ "step": 1080
1523
+ },
1524
+ {
1525
+ "epoch": 0.6047516198704104,
1526
+ "grad_norm": 1.192563533782959,
1527
+ "learning_rate": 4.06691531577047e-05,
1528
+ "loss": 1.5983,
1529
+ "step": 1085
1530
+ },
1531
+ {
1532
+ "epoch": 0.6075384936946979,
1533
+ "grad_norm": 1.0872273445129395,
1534
+ "learning_rate": 4.019183059598296e-05,
1535
+ "loss": 1.556,
1536
+ "step": 1090
1537
+ },
1538
+ {
1539
+ "epoch": 0.6103253675189856,
1540
+ "grad_norm": 1.0830320119857788,
1541
+ "learning_rate": 3.971543588738724e-05,
1542
+ "loss": 1.5684,
1543
+ "step": 1095
1544
+ },
1545
+ {
1546
+ "epoch": 0.6131122413432731,
1547
+ "grad_norm": 1.169758677482605,
1548
+ "learning_rate": 3.924001409887158e-05,
1549
+ "loss": 1.5279,
1550
+ "step": 1100
1551
+ },
1552
+ {
1553
+ "epoch": 0.6158991151675608,
1554
+ "grad_norm": 1.1774030923843384,
1555
+ "learning_rate": 3.87656102053517e-05,
1556
+ "loss": 1.5961,
1557
+ "step": 1105
1558
+ },
1559
+ {
1560
+ "epoch": 0.6186859889918483,
1561
+ "grad_norm": 1.0763884782791138,
1562
+ "learning_rate": 3.8292269085450474e-05,
1563
+ "loss": 1.551,
1564
+ "step": 1110
1565
+ },
1566
+ {
1567
+ "epoch": 0.621472862816136,
1568
+ "grad_norm": 1.075225830078125,
1569
+ "learning_rate": 3.782003551725236e-05,
1570
+ "loss": 1.6487,
1571
+ "step": 1115
1572
+ },
1573
+ {
1574
+ "epoch": 0.6242597366404236,
1575
+ "grad_norm": 1.0965514183044434,
1576
+ "learning_rate": 3.734895417406734e-05,
1577
+ "loss": 1.6189,
1578
+ "step": 1120
1579
+ },
1580
+ {
1581
+ "epoch": 0.6270466104647112,
1582
+ "grad_norm": 1.1394857168197632,
1583
+ "learning_rate": 3.687906962020491e-05,
1584
+ "loss": 1.6158,
1585
+ "step": 1125
1586
+ },
1587
+ {
1588
+ "epoch": 0.6298334842889988,
1589
+ "grad_norm": 1.2145012617111206,
1590
+ "learning_rate": 3.641042630675829e-05,
1591
+ "loss": 1.6272,
1592
+ "step": 1130
1593
+ },
1594
+ {
1595
+ "epoch": 0.6326203581132864,
1596
+ "grad_norm": 1.1138585805892944,
1597
+ "learning_rate": 3.594306856739924e-05,
1598
+ "loss": 1.5412,
1599
+ "step": 1135
1600
+ },
1601
+ {
1602
+ "epoch": 0.635407231937574,
1603
+ "grad_norm": 1.0962103605270386,
1604
+ "learning_rate": 3.547704061418424e-05,
1605
+ "loss": 1.5695,
1606
+ "step": 1140
1607
+ },
1608
+ {
1609
+ "epoch": 0.6381941057618616,
1610
+ "grad_norm": 1.211378574371338,
1611
+ "learning_rate": 3.501238653337194e-05,
1612
+ "loss": 1.5873,
1613
+ "step": 1145
1614
+ },
1615
+ {
1616
+ "epoch": 0.6409809795861492,
1617
+ "grad_norm": 1.2112855911254883,
1618
+ "learning_rate": 3.4549150281252636e-05,
1619
+ "loss": 1.6429,
1620
+ "step": 1150
1621
+ },
1622
+ {
1623
+ "epoch": 0.6437678534104369,
1624
+ "grad_norm": 1.0879449844360352,
1625
+ "learning_rate": 3.408737567998993e-05,
1626
+ "loss": 1.4743,
1627
+ "step": 1155
1628
+ },
1629
+ {
1630
+ "epoch": 0.6465547272347244,
1631
+ "grad_norm": 1.1650608777999878,
1632
+ "learning_rate": 3.362710641347524e-05,
1633
+ "loss": 1.6351,
1634
+ "step": 1160
1635
+ },
1636
+ {
1637
+ "epoch": 0.6493416010590121,
1638
+ "grad_norm": 1.1134223937988281,
1639
+ "learning_rate": 3.316838602319532e-05,
1640
+ "loss": 1.6253,
1641
+ "step": 1165
1642
+ },
1643
+ {
1644
+ "epoch": 0.6521284748832996,
1645
+ "grad_norm": 1.1670359373092651,
1646
+ "learning_rate": 3.271125790411309e-05,
1647
+ "loss": 1.4708,
1648
+ "step": 1170
1649
+ },
1650
+ {
1651
+ "epoch": 0.6549153487075873,
1652
+ "grad_norm": 1.2295384407043457,
1653
+ "learning_rate": 3.225576530056264e-05,
1654
+ "loss": 1.6296,
1655
+ "step": 1175
1656
+ },
1657
+ {
1658
+ "epoch": 0.6577022225318748,
1659
+ "grad_norm": 1.1380615234375,
1660
+ "learning_rate": 3.180195130215824e-05,
1661
+ "loss": 1.5968,
1662
+ "step": 1180
1663
+ },
1664
+ {
1665
+ "epoch": 0.6604890963561625,
1666
+ "grad_norm": 1.2421152591705322,
1667
+ "learning_rate": 3.1349858839717986e-05,
1668
+ "loss": 1.5466,
1669
+ "step": 1185
1670
+ },
1671
+ {
1672
+ "epoch": 0.66327597018045,
1673
+ "grad_norm": 1.2051341533660889,
1674
+ "learning_rate": 3.089953068120271e-05,
1675
+ "loss": 1.5015,
1676
+ "step": 1190
1677
+ },
1678
+ {
1679
+ "epoch": 0.6660628440047377,
1680
+ "grad_norm": 1.1928534507751465,
1681
+ "learning_rate": 3.0451009427669986e-05,
1682
+ "loss": 1.5243,
1683
+ "step": 1195
1684
+ },
1685
+ {
1686
+ "epoch": 0.6688497178290252,
1687
+ "grad_norm": 1.1529725790023804,
1688
+ "learning_rate": 3.000433750924414e-05,
1689
+ "loss": 1.5789,
1690
+ "step": 1200
1691
+ },
1692
+ {
1693
+ "epoch": 0.6716365916533129,
1694
+ "grad_norm": 1.0926425457000732,
1695
+ "learning_rate": 2.9559557181102315e-05,
1696
+ "loss": 1.5873,
1697
+ "step": 1205
1698
+ },
1699
+ {
1700
+ "epoch": 0.6744234654776005,
1701
+ "grad_norm": 1.2585104703903198,
1702
+ "learning_rate": 2.911671051947722e-05,
1703
+ "loss": 1.5098,
1704
+ "step": 1210
1705
+ },
1706
+ {
1707
+ "epoch": 0.6772103393018881,
1708
+ "grad_norm": 1.2193644046783447,
1709
+ "learning_rate": 2.867583941767657e-05,
1710
+ "loss": 1.5172,
1711
+ "step": 1215
1712
+ },
1713
+ {
1714
+ "epoch": 0.6799972131261757,
1715
+ "grad_norm": 1.1319342851638794,
1716
+ "learning_rate": 2.823698558212009e-05,
1717
+ "loss": 1.5894,
1718
+ "step": 1220
1719
+ },
1720
+ {
1721
+ "epoch": 0.6827840869504633,
1722
+ "grad_norm": 1.224010705947876,
1723
+ "learning_rate": 2.7800190528394122e-05,
1724
+ "loss": 1.5454,
1725
+ "step": 1225
1726
+ },
1727
+ {
1728
+ "epoch": 0.6855709607747509,
1729
+ "grad_norm": 1.1011543273925781,
1730
+ "learning_rate": 2.736549557732405e-05,
1731
+ "loss": 1.5201,
1732
+ "step": 1230
1733
+ },
1734
+ {
1735
+ "epoch": 0.6883578345990385,
1736
+ "grad_norm": 1.129728078842163,
1737
+ "learning_rate": 2.693294185106562e-05,
1738
+ "loss": 1.7555,
1739
+ "step": 1235
1740
+ },
1741
+ {
1742
+ "epoch": 0.6911447084233261,
1743
+ "grad_norm": 1.1907600164413452,
1744
+ "learning_rate": 2.650257026921455e-05,
1745
+ "loss": 1.5952,
1746
+ "step": 1240
1747
+ },
1748
+ {
1749
+ "epoch": 0.6939315822476138,
1750
+ "grad_norm": 1.2378222942352295,
1751
+ "learning_rate": 2.607442154493568e-05,
1752
+ "loss": 1.6424,
1753
+ "step": 1245
1754
+ },
1755
+ {
1756
+ "epoch": 0.6967184560719013,
1757
+ "grad_norm": 1.2243040800094604,
1758
+ "learning_rate": 2.5648536181111438e-05,
1759
+ "loss": 1.5787,
1760
+ "step": 1250
1761
+ },
1762
+ {
1763
+ "epoch": 0.699505329896189,
1764
+ "grad_norm": 1.197749376296997,
1765
+ "learning_rate": 2.5224954466510274e-05,
1766
+ "loss": 1.5643,
1767
+ "step": 1255
1768
+ },
1769
+ {
1770
+ "epoch": 0.7022922037204765,
1771
+ "grad_norm": 1.1655267477035522,
1772
+ "learning_rate": 2.480371647197538e-05,
1773
+ "loss": 1.6219,
1774
+ "step": 1260
1775
+ },
1776
+ {
1777
+ "epoch": 0.7050790775447642,
1778
+ "grad_norm": 1.1615575551986694,
1779
+ "learning_rate": 2.438486204663391e-05,
1780
+ "loss": 1.6377,
1781
+ "step": 1265
1782
+ },
1783
+ {
1784
+ "epoch": 0.7078659513690517,
1785
+ "grad_norm": 1.1524951457977295,
1786
+ "learning_rate": 2.3968430814127385e-05,
1787
+ "loss": 1.5994,
1788
+ "step": 1270
1789
+ },
1790
+ {
1791
+ "epoch": 0.7106528251933394,
1792
+ "grad_norm": 1.177948236465454,
1793
+ "learning_rate": 2.3554462168863085e-05,
1794
+ "loss": 1.5988,
1795
+ "step": 1275
1796
+ },
1797
+ {
1798
+ "epoch": 0.7134396990176269,
1799
+ "grad_norm": 1.1656767129898071,
1800
+ "learning_rate": 2.314299527228759e-05,
1801
+ "loss": 1.5991,
1802
+ "step": 1280
1803
+ },
1804
+ {
1805
+ "epoch": 0.7162265728419146,
1806
+ "grad_norm": 1.1447503566741943,
1807
+ "learning_rate": 2.2734069049181882e-05,
1808
+ "loss": 1.552,
1809
+ "step": 1285
1810
+ },
1811
+ {
1812
+ "epoch": 0.7190134466662021,
1813
+ "grad_norm": 1.1773953437805176,
1814
+ "learning_rate": 2.2327722183979212e-05,
1815
+ "loss": 1.5824,
1816
+ "step": 1290
1817
+ },
1818
+ {
1819
+ "epoch": 0.7218003204904898,
1820
+ "grad_norm": 1.2031999826431274,
1821
+ "learning_rate": 2.1923993117105462e-05,
1822
+ "loss": 1.5542,
1823
+ "step": 1295
1824
+ },
1825
+ {
1826
+ "epoch": 0.7245871943147774,
1827
+ "grad_norm": 1.2782498598098755,
1828
+ "learning_rate": 2.1522920041342704e-05,
1829
+ "loss": 1.5622,
1830
+ "step": 1300
1831
+ },
1832
+ {
1833
+ "epoch": 0.727374068139065,
1834
+ "grad_norm": 1.2838361263275146,
1835
+ "learning_rate": 2.1124540898216248e-05,
1836
+ "loss": 1.6137,
1837
+ "step": 1305
1838
+ },
1839
+ {
1840
+ "epoch": 0.7301609419633526,
1841
+ "grad_norm": 1.0898470878601074,
1842
+ "learning_rate": 2.0728893374405166e-05,
1843
+ "loss": 1.4883,
1844
+ "step": 1310
1845
+ },
1846
+ {
1847
+ "epoch": 0.7329478157876402,
1848
+ "grad_norm": 1.2910934686660767,
1849
+ "learning_rate": 2.033601489817738e-05,
1850
+ "loss": 1.6914,
1851
+ "step": 1315
1852
+ },
1853
+ {
1854
+ "epoch": 0.7357346896119278,
1855
+ "grad_norm": 1.1973011493682861,
1856
+ "learning_rate": 1.9945942635848748e-05,
1857
+ "loss": 1.6045,
1858
+ "step": 1320
1859
+ },
1860
+ {
1861
+ "epoch": 0.7385215634362154,
1862
+ "grad_norm": 1.1607261896133423,
1863
+ "learning_rate": 1.9558713488267238e-05,
1864
+ "loss": 1.6271,
1865
+ "step": 1325
1866
+ },
1867
+ {
1868
+ "epoch": 0.741308437260503,
1869
+ "grad_norm": 1.1561816930770874,
1870
+ "learning_rate": 1.917436408732208e-05,
1871
+ "loss": 1.5863,
1872
+ "step": 1330
1873
+ },
1874
+ {
1875
+ "epoch": 0.7440953110847907,
1876
+ "grad_norm": 1.3082060813903809,
1877
+ "learning_rate": 1.8792930792478357e-05,
1878
+ "loss": 1.5784,
1879
+ "step": 1335
1880
+ },
1881
+ {
1882
+ "epoch": 0.7468821849090782,
1883
+ "grad_norm": 1.2375142574310303,
1884
+ "learning_rate": 1.8414449687337464e-05,
1885
+ "loss": 1.5183,
1886
+ "step": 1340
1887
+ },
1888
+ {
1889
+ "epoch": 0.7496690587333659,
1890
+ "grad_norm": 1.1608905792236328,
1891
+ "learning_rate": 1.8038956576223504e-05,
1892
+ "loss": 1.4922,
1893
+ "step": 1345
1894
+ },
1895
+ {
1896
+ "epoch": 0.7524559325576534,
1897
+ "grad_norm": 1.115347146987915,
1898
+ "learning_rate": 1.766648698079635e-05,
1899
+ "loss": 1.5755,
1900
+ "step": 1350
1901
+ },
1902
+ {
1903
+ "epoch": 0.7552428063819411,
1904
+ "grad_norm": 1.1984525918960571,
1905
+ "learning_rate": 1.7297076136691072e-05,
1906
+ "loss": 1.6937,
1907
+ "step": 1355
1908
+ },
1909
+ {
1910
+ "epoch": 0.7580296802062286,
1911
+ "grad_norm": 1.303263545036316,
1912
+ "learning_rate": 1.6930758990184875e-05,
1913
+ "loss": 1.5859,
1914
+ "step": 1360
1915
+ },
1916
+ {
1917
+ "epoch": 0.7608165540305163,
1918
+ "grad_norm": 1.3034437894821167,
1919
+ "learning_rate": 1.6567570194891024e-05,
1920
+ "loss": 1.5933,
1921
+ "step": 1365
1922
+ },
1923
+ {
1924
+ "epoch": 0.7636034278548038,
1925
+ "grad_norm": 1.3601844310760498,
1926
+ "learning_rate": 1.620754410848069e-05,
1927
+ "loss": 1.6024,
1928
+ "step": 1370
1929
+ },
1930
+ {
1931
+ "epoch": 0.7663903016790915,
1932
+ "grad_norm": 1.1310255527496338,
1933
+ "learning_rate": 1.5850714789432663e-05,
1934
+ "loss": 1.6289,
1935
+ "step": 1375
1936
+ },
1937
+ {
1938
+ "epoch": 0.769177175503379,
1939
+ "grad_norm": 1.2622790336608887,
1940
+ "learning_rate": 1.549711599381145e-05,
1941
+ "loss": 1.6036,
1942
+ "step": 1380
1943
+ },
1944
+ {
1945
+ "epoch": 0.7719640493276667,
1946
+ "grad_norm": 1.083112120628357,
1947
+ "learning_rate": 1.5146781172073959e-05,
1948
+ "loss": 1.5315,
1949
+ "step": 1385
1950
+ },
1951
+ {
1952
+ "epoch": 0.7747509231519543,
1953
+ "grad_norm": 1.148478388786316,
1954
+ "learning_rate": 1.479974346590503e-05,
1955
+ "loss": 1.5547,
1956
+ "step": 1390
1957
+ },
1958
+ {
1959
+ "epoch": 0.7775377969762419,
1960
+ "grad_norm": 1.2147221565246582,
1961
+ "learning_rate": 1.4456035705082349e-05,
1962
+ "loss": 1.547,
1963
+ "step": 1395
1964
+ },
1965
+ {
1966
+ "epoch": 0.7803246708005295,
1967
+ "grad_norm": 1.2222541570663452,
1968
+ "learning_rate": 1.4115690404370551e-05,
1969
+ "loss": 1.5699,
1970
+ "step": 1400
1971
+ },
1972
+ {
1973
+ "epoch": 0.7831115446248171,
1974
+ "grad_norm": 1.1956994533538818,
1975
+ "learning_rate": 1.3778739760445552e-05,
1976
+ "loss": 1.5662,
1977
+ "step": 1405
1978
+ },
1979
+ {
1980
+ "epoch": 0.7858984184491047,
1981
+ "grad_norm": 1.2326176166534424,
1982
+ "learning_rate": 1.344521564884858e-05,
1983
+ "loss": 1.651,
1984
+ "step": 1410
1985
+ },
1986
+ {
1987
+ "epoch": 0.7886852922733923,
1988
+ "grad_norm": 1.105504035949707,
1989
+ "learning_rate": 1.3115149620970795e-05,
1990
+ "loss": 1.6314,
1991
+ "step": 1415
1992
+ },
1993
+ {
1994
+ "epoch": 0.7914721660976799,
1995
+ "grad_norm": 1.242881417274475,
1996
+ "learning_rate": 1.2788572901068552e-05,
1997
+ "loss": 1.5533,
1998
+ "step": 1420
1999
+ },
2000
+ {
2001
+ "epoch": 0.7942590399219676,
2002
+ "grad_norm": 1.3160309791564941,
2003
+ "learning_rate": 1.2465516383309551e-05,
2004
+ "loss": 1.5956,
2005
+ "step": 1425
2006
+ },
2007
+ {
2008
+ "epoch": 0.7970459137462551,
2009
+ "grad_norm": 1.182173728942871,
2010
+ "learning_rate": 1.2146010628850268e-05,
2011
+ "loss": 1.6278,
2012
+ "step": 1430
2013
+ },
2014
+ {
2015
+ "epoch": 0.7998327875705428,
2016
+ "grad_norm": 1.1472742557525635,
2017
+ "learning_rate": 1.183008586294485e-05,
2018
+ "loss": 1.5435,
2019
+ "step": 1435
2020
+ },
2021
+ {
2022
+ "epoch": 0.8026196613948303,
2023
+ "grad_norm": 1.1797904968261719,
2024
+ "learning_rate": 1.151777197208585e-05,
2025
+ "loss": 1.5575,
2026
+ "step": 1440
2027
+ },
2028
+ {
2029
+ "epoch": 0.805406535219118,
2030
+ "grad_norm": 1.222711443901062,
2031
+ "learning_rate": 1.1209098501176896e-05,
2032
+ "loss": 1.5422,
2033
+ "step": 1445
2034
+ },
2035
+ {
2036
+ "epoch": 0.8081934090434055,
2037
+ "grad_norm": 1.207819938659668,
2038
+ "learning_rate": 1.0904094650737795e-05,
2039
+ "loss": 1.5574,
2040
+ "step": 1450
2041
+ },
2042
+ {
2043
+ "epoch": 0.8109802828676932,
2044
+ "grad_norm": 1.3372864723205566,
2045
+ "learning_rate": 1.0602789274142133e-05,
2046
+ "loss": 1.6103,
2047
+ "step": 1455
2048
+ },
2049
+ {
2050
+ "epoch": 0.8137671566919807,
2051
+ "grad_norm": 1.1970205307006836,
2052
+ "learning_rate": 1.0305210874887766e-05,
2053
+ "loss": 1.4813,
2054
+ "step": 1460
2055
+ },
2056
+ {
2057
+ "epoch": 0.8165540305162684,
2058
+ "grad_norm": 1.1915411949157715,
2059
+ "learning_rate": 1.0011387603900385e-05,
2060
+ "loss": 1.5635,
2061
+ "step": 1465
2062
+ },
2063
+ {
2064
+ "epoch": 0.819340904340556,
2065
+ "grad_norm": 1.1929457187652588,
2066
+ "learning_rate": 9.7213472568704e-06,
2067
+ "loss": 1.5771,
2068
+ "step": 1470
2069
+ },
2070
+ {
2071
+ "epoch": 0.8221277781648436,
2072
+ "grad_norm": 1.2298965454101562,
2073
+ "learning_rate": 9.435117271623566e-06,
2074
+ "loss": 1.4333,
2075
+ "step": 1475
2076
+ },
2077
+ {
2078
+ "epoch": 0.8249146519891312,
2079
+ "grad_norm": 1.2105895280838013,
2080
+ "learning_rate": 9.152724725525202e-06,
2081
+ "loss": 1.5834,
2082
+ "step": 1480
2083
+ },
2084
+ {
2085
+ "epoch": 0.8277015258134188,
2086
+ "grad_norm": 1.0827617645263672,
2087
+ "learning_rate": 8.87419633291886e-06,
2088
+ "loss": 1.6125,
2089
+ "step": 1485
2090
+ },
2091
+ {
2092
+ "epoch": 0.8304883996377064,
2093
+ "grad_norm": 1.270128607749939,
2094
+ "learning_rate": 8.599558442598998e-06,
2095
+ "loss": 1.5189,
2096
+ "step": 1490
2097
+ },
2098
+ {
2099
+ "epoch": 0.833275273461994,
2100
+ "grad_norm": 1.3602410554885864,
2101
+ "learning_rate": 8.328837035318448e-06,
2102
+ "loss": 1.6231,
2103
+ "step": 1495
2104
+ },
2105
+ {
2106
+ "epoch": 0.8360621472862816,
2107
+ "grad_norm": 1.147322177886963,
2108
+ "learning_rate": 8.06205772133063e-06,
2109
+ "loss": 1.4859,
2110
+ "step": 1500
2111
+ }
2112
+ ],
2113
+ "logging_steps": 5,
2114
+ "max_steps": 1795,
2115
+ "num_input_tokens_seen": 0,
2116
+ "num_train_epochs": 1,
2117
+ "save_steps": 500,
2118
+ "stateful_callbacks": {
2119
+ "TrainerControl": {
2120
+ "args": {
2121
+ "should_epoch_stop": false,
2122
+ "should_evaluate": false,
2123
+ "should_log": false,
2124
+ "should_save": true,
2125
+ "should_training_stop": false
2126
+ },
2127
+ "attributes": {}
2128
+ }
2129
+ },
2130
+ "total_flos": 1.1447072533289088e+17,
2131
+ "train_batch_size": 1,
2132
+ "trial_name": null,
2133
+ "trial_params": null
2134
+ }
checkpoint-1500/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e1aa320b63b839db302f62b6b9c4d585113c78963c721e06eb11dc1a03601f4f
3
+ size 6161
checkpoint-1795/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: google/gemma-3-4b-it
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.15.2
checkpoint-1795/adapter_config.json ADDED
@@ -0,0 +1,138 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "google/gemma-3-4b-it",
5
+ "bias": "none",
6
+ "corda_config": null,
7
+ "eva_config": null,
8
+ "exclude_modules": null,
9
+ "fan_in_fan_out": false,
10
+ "inference_mode": true,
11
+ "init_lora_weights": true,
12
+ "layer_replication": null,
13
+ "layers_pattern": null,
14
+ "layers_to_transform": null,
15
+ "loftq_config": {},
16
+ "lora_alpha": 16,
17
+ "lora_bias": false,
18
+ "lora_dropout": 0.0,
19
+ "megatron_config": null,
20
+ "megatron_core": "megatron.core",
21
+ "modules_to_save": null,
22
+ "peft_type": "LORA",
23
+ "r": 8,
24
+ "rank_pattern": {},
25
+ "revision": null,
26
+ "target_modules": [
27
+ "language_model.layers.13.self_attn.q_proj",
28
+ "language_model.layers.11.self_attn.k_proj",
29
+ "language_model.layers.7.self_attn.k_proj",
30
+ "language_model.layers.15.self_attn.v_proj",
31
+ "language_model.layers.15.self_attn.k_proj",
32
+ "language_model.layers.26.self_attn.v_proj",
33
+ "o_proj",
34
+ "language_model.layers.7.self_attn.v_proj",
35
+ "32.self_attn.k_proj",
36
+ "27.self_attn.q_proj",
37
+ "language_model.layers.14.self_attn.q_proj",
38
+ "language_model.layers.6.self_attn.q_proj",
39
+ "33.self_attn.q_proj",
40
+ "language_model.layers.13.self_attn.v_proj",
41
+ "language_model.layers.18.self_attn.q_proj",
42
+ "language_model.layers.11.self_attn.q_proj",
43
+ "28.self_attn.q_proj",
44
+ "language_model.layers.19.self_attn.q_proj",
45
+ "27.self_attn.v_proj",
46
+ "language_model.layers.24.self_attn.q_proj",
47
+ "language_model.layers.22.self_attn.k_proj",
48
+ "language_model.layers.25.self_attn.v_proj",
49
+ "language_model.layers.26.self_attn.q_proj",
50
+ "29.self_attn.k_proj",
51
+ "language_model.layers.24.self_attn.k_proj",
52
+ "language_model.layers.25.self_attn.q_proj",
53
+ "down_proj",
54
+ "language_model.layers.20.self_attn.q_proj",
55
+ "language_model.layers.10.self_attn.v_proj",
56
+ "30.self_attn.q_proj",
57
+ "33.self_attn.v_proj",
58
+ "language_model.layers.4.self_attn.q_proj",
59
+ "language_model.layers.18.self_attn.v_proj",
60
+ "31.self_attn.q_proj",
61
+ "33.self_attn.k_proj",
62
+ "language_model.layers.24.self_attn.v_proj",
63
+ "language_model.layers.23.self_attn.k_proj",
64
+ "language_model.layers.17.self_attn.k_proj",
65
+ "language_model.layers.0.self_attn.q_proj",
66
+ "language_model.layers.10.self_attn.q_proj",
67
+ "29.self_attn.v_proj",
68
+ "language_model.layers.1.self_attn.q_proj",
69
+ "30.self_attn.k_proj",
70
+ "language_model.layers.6.self_attn.k_proj",
71
+ "language_model.layers.1.self_attn.v_proj",
72
+ "28.self_attn.v_proj",
73
+ "language_model.layers.4.self_attn.v_proj",
74
+ "language_model.layers.0.self_attn.k_proj",
75
+ "30.self_attn.v_proj",
76
+ "28.self_attn.k_proj",
77
+ "language_model.layers.9.self_attn.v_proj",
78
+ "gate_proj",
79
+ "language_model.layers.4.self_attn.k_proj",
80
+ "language_model.layers.26.self_attn.k_proj",
81
+ "language_model.layers.3.self_attn.q_proj",
82
+ "language_model.layers.20.self_attn.v_proj",
83
+ "language_model.layers.5.self_attn.q_proj",
84
+ "language_model.layers.8.self_attn.q_proj",
85
+ "language_model.layers.16.self_attn.k_proj",
86
+ "language_model.layers.12.self_attn.k_proj",
87
+ "language_model.layers.2.self_attn.v_proj",
88
+ "language_model.layers.6.self_attn.v_proj",
89
+ "language_model.layers.12.self_attn.q_proj",
90
+ "language_model.layers.17.self_attn.v_proj",
91
+ "31.self_attn.v_proj",
92
+ "language_model.layers.16.self_attn.v_proj",
93
+ "language_model.layers.20.self_attn.k_proj",
94
+ "language_model.layers.12.self_attn.v_proj",
95
+ "language_model.layers.3.self_attn.k_proj",
96
+ "language_model.layers.8.self_attn.v_proj",
97
+ "language_model.layers.3.self_attn.v_proj",
98
+ "32.self_attn.v_proj",
99
+ "27.self_attn.k_proj",
100
+ "language_model.layers.5.self_attn.v_proj",
101
+ "language_model.layers.10.self_attn.k_proj",
102
+ "31.self_attn.k_proj",
103
+ "language_model.layers.16.self_attn.q_proj",
104
+ "language_model.layers.22.self_attn.v_proj",
105
+ "language_model.layers.9.self_attn.k_proj",
106
+ "language_model.layers.2.self_attn.q_proj",
107
+ "language_model.layers.19.self_attn.k_proj",
108
+ "language_model.layers.2.self_attn.k_proj",
109
+ "language_model.layers.23.self_attn.v_proj",
110
+ "language_model.layers.9.self_attn.q_proj",
111
+ "language_model.layers.14.self_attn.v_proj",
112
+ "language_model.layers.0.self_attn.v_proj",
113
+ "language_model.layers.21.self_attn.v_proj",
114
+ "language_model.layers.19.self_attn.v_proj",
115
+ "29.self_attn.q_proj",
116
+ "language_model.layers.15.self_attn.q_proj",
117
+ "language_model.layers.22.self_attn.q_proj",
118
+ "language_model.layers.21.self_attn.q_proj",
119
+ "language_model.layers.17.self_attn.q_proj",
120
+ "language_model.layers.11.self_attn.v_proj",
121
+ "language_model.layers.18.self_attn.k_proj",
122
+ "language_model.layers.25.self_attn.k_proj",
123
+ "language_model.layers.7.self_attn.q_proj",
124
+ "32.self_attn.q_proj",
125
+ "language_model.layers.23.self_attn.q_proj",
126
+ "language_model.layers.21.self_attn.k_proj",
127
+ "language_model.layers.5.self_attn.k_proj",
128
+ "language_model.layers.8.self_attn.k_proj",
129
+ "language_model.layers.13.self_attn.k_proj",
130
+ "up_proj",
131
+ "language_model.layers.1.self_attn.k_proj",
132
+ "language_model.layers.14.self_attn.k_proj"
133
+ ],
134
+ "task_type": "CAUSAL_LM",
135
+ "trainable_token_indices": null,
136
+ "use_dora": false,
137
+ "use_rslora": false
138
+ }
checkpoint-1795/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:14e9e7343d876dd5bfa1c7a89e5fb9c90e9aae4cc3e14dd5e546f880a54d0543
3
+ size 59675008
checkpoint-1795/added_tokens.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ {
2
+ "<image_soft_token>": 262144
3
+ }
checkpoint-1795/chat_template.jinja ADDED
@@ -0,0 +1,47 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {{ bos_token }}
2
+ {%- if messages[0]['role'] == 'system' -%}
3
+ {%- if messages[0]['content'] is string -%}
4
+ {%- set first_user_prefix = messages[0]['content'] + '
5
+
6
+ ' -%}
7
+ {%- else -%}
8
+ {%- set first_user_prefix = messages[0]['content'][0]['text'] + '
9
+
10
+ ' -%}
11
+ {%- endif -%}
12
+ {%- set loop_messages = messages[1:] -%}
13
+ {%- else -%}
14
+ {%- set first_user_prefix = "" -%}
15
+ {%- set loop_messages = messages -%}
16
+ {%- endif -%}
17
+ {%- for message in loop_messages -%}
18
+ {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}
19
+ {{ raise_exception("Conversation roles must alternate user/assistant/user/assistant/...") }}
20
+ {%- endif -%}
21
+ {%- if (message['role'] == 'assistant') -%}
22
+ {%- set role = "model" -%}
23
+ {%- else -%}
24
+ {%- set role = message['role'] -%}
25
+ {%- endif -%}
26
+ {{ '<start_of_turn>' + role + '
27
+ ' + (first_user_prefix if loop.first else "") }}
28
+ {%- if message['content'] is string -%}
29
+ {{ message['content'] | trim }}
30
+ {%- elif message['content'] is iterable -%}
31
+ {%- for item in message['content'] -%}
32
+ {%- if item['type'] == 'image' -%}
33
+ {{ '<start_of_image>' }}
34
+ {%- elif item['type'] == 'text' -%}
35
+ {{ item['text'] | trim }}
36
+ {%- endif -%}
37
+ {%- endfor -%}
38
+ {%- else -%}
39
+ {{ raise_exception("Invalid content type") }}
40
+ {%- endif -%}
41
+ {{ '<end_of_turn>
42
+ ' }}
43
+ {%- endfor -%}
44
+ {%- if add_generation_prompt -%}
45
+ {{'<start_of_turn>model
46
+ '}}
47
+ {%- endif -%}
checkpoint-1795/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:05e6312d08418c1efbb30e9d492ff5a496c48327f358fba7c50ff48aa3d20a37
3
+ size 119611063
checkpoint-1795/preprocessor_config.json ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "do_convert_rgb": null,
3
+ "do_normalize": true,
4
+ "do_pan_and_scan": null,
5
+ "do_rescale": true,
6
+ "do_resize": true,
7
+ "image_mean": [
8
+ 0.5,
9
+ 0.5,
10
+ 0.5
11
+ ],
12
+ "image_processor_type": "Gemma3ImageProcessor",
13
+ "image_seq_length": 256,
14
+ "image_std": [
15
+ 0.5,
16
+ 0.5,
17
+ 0.5
18
+ ],
19
+ "pan_and_scan_max_num_crops": null,
20
+ "pan_and_scan_min_crop_size": null,
21
+ "pan_and_scan_min_ratio_to_activate": null,
22
+ "processor_class": "Gemma3Processor",
23
+ "resample": 2,
24
+ "rescale_factor": 0.00392156862745098,
25
+ "size": {
26
+ "height": 896,
27
+ "width": 896
28
+ }
29
+ }
checkpoint-1795/processor_config.json ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ {
2
+ "image_seq_length": 256,
3
+ "processor_class": "Gemma3Processor"
4
+ }
checkpoint-1795/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:250560ab3d528161ab3659b120def6e4a9ab4b457e3399603bbcfa40db3efc90
3
+ size 14645
checkpoint-1795/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e1eb2e719ba92d61c300d3b21bda51012661191790b1797109a6a81ec3f6ab06
3
+ size 1465
checkpoint-1795/special_tokens_map.json ADDED
@@ -0,0 +1,33 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "boi_token": "<start_of_image>",
3
+ "bos_token": {
4
+ "content": "<bos>",
5
+ "lstrip": false,
6
+ "normalized": false,
7
+ "rstrip": false,
8
+ "single_word": false
9
+ },
10
+ "eoi_token": "<end_of_image>",
11
+ "eos_token": {
12
+ "content": "<end_of_turn>",
13
+ "lstrip": false,
14
+ "normalized": false,
15
+ "rstrip": false,
16
+ "single_word": false
17
+ },
18
+ "image_token": "<image_soft_token>",
19
+ "pad_token": {
20
+ "content": "<pad>",
21
+ "lstrip": false,
22
+ "normalized": false,
23
+ "rstrip": false,
24
+ "single_word": false
25
+ },
26
+ "unk_token": {
27
+ "content": "<unk>",
28
+ "lstrip": false,
29
+ "normalized": false,
30
+ "rstrip": false,
31
+ "single_word": false
32
+ }
33
+ }