akseljoonas HF Staff commited on
Commit
6614cad
·
verified ·
1 Parent(s): 8529855

Model save

Browse files
README.md ADDED
@@ -0,0 +1,58 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: Qwen/Qwen2.5-3B-Instruct
3
+ library_name: transformers
4
+ model_name: Agentic-Qwen-3B-e12-lr3-b8
5
+ tags:
6
+ - generated_from_trainer
7
+ - trl
8
+ - sft
9
+ licence: license
10
+ ---
11
+
12
+ # Model Card for Agentic-Qwen-3B-e12-lr3-b8
13
+
14
+ This model is a fine-tuned version of [Qwen/Qwen2.5-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-3B-Instruct).
15
+ It has been trained using [TRL](https://github.com/huggingface/trl).
16
+
17
+ ## Quick start
18
+
19
+ ```python
20
+ from transformers import pipeline
21
+
22
+ question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
23
+ generator = pipeline("text-generation", model="akseljoonas/Agentic-Qwen-3B-e12-lr3-b8", device="cuda")
24
+ output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
25
+ print(output["generated_text"])
26
+ ```
27
+
28
+ ## Training procedure
29
+
30
+ [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/akseljoonas-university-of-groningen/huggingface/runs/khmq58rv)
31
+
32
+
33
+ This model was trained with SFT.
34
+
35
+ ### Framework versions
36
+
37
+ - TRL: 0.16.0
38
+ - Transformers: 4.50.0
39
+ - Pytorch: 2.6.0
40
+ - Datasets: 3.5.0
41
+ - Tokenizers: 0.21.1
42
+
43
+ ## Citations
44
+
45
+
46
+
47
+ Cite TRL as:
48
+
49
+ ```bibtex
50
+ @misc{vonwerra2022trl,
51
+ title = {{TRL: Transformer Reinforcement Learning}},
52
+ author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec},
53
+ year = 2020,
54
+ journal = {GitHub repository},
55
+ publisher = {GitHub},
56
+ howpublished = {\url{https://github.com/huggingface/trl}}
57
+ }
58
+ ```
all_results.json ADDED
@@ -0,0 +1,8 @@
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "total_flos": 68866778333184.0,
3
+ "train_loss": 0.5774029536793629,
4
+ "train_runtime": 585.0314,
5
+ "train_samples": 1928,
6
+ "train_samples_per_second": 11.056,
7
+ "train_steps_per_second": 0.164
8
+ }
generation_config.json ADDED
@@ -0,0 +1,14 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bos_token_id": 151643,
3
+ "do_sample": true,
4
+ "eos_token_id": [
5
+ 151645,
6
+ 151643
7
+ ],
8
+ "pad_token_id": 151643,
9
+ "repetition_penalty": 1.05,
10
+ "temperature": 0.7,
11
+ "top_k": 20,
12
+ "top_p": 0.8,
13
+ "transformers_version": "4.50.0"
14
+ }
train_results.json ADDED
@@ -0,0 +1,8 @@
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "total_flos": 68866778333184.0,
3
+ "train_loss": 0.5774029536793629,
4
+ "train_runtime": 585.0314,
5
+ "train_samples": 1928,
6
+ "train_samples_per_second": 11.056,
7
+ "train_steps_per_second": 0.164
8
+ }
trainer_state.json ADDED
@@ -0,0 +1,216 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_global_step": null,
3
+ "best_metric": null,
4
+ "best_model_checkpoint": null,
5
+ "epoch": 10.705882352941176,
6
+ "eval_steps": 500,
7
+ "global_step": 96,
8
+ "is_hyper_param_search": false,
9
+ "is_local_process_zero": true,
10
+ "is_world_process_zero": true,
11
+ "log_history": [
12
+ {
13
+ "epoch": 0.5882352941176471,
14
+ "grad_norm": 0.9883961465327094,
15
+ "learning_rate": 1.5e-05,
16
+ "loss": 1.1572,
17
+ "mean_token_accuracy": 0.7539515912532806,
18
+ "num_tokens": 2505918.0,
19
+ "step": 5
20
+ },
21
+ {
22
+ "epoch": 1.1176470588235294,
23
+ "grad_norm": 1.901663288130973,
24
+ "learning_rate": 3e-05,
25
+ "loss": 1.0333,
26
+ "mean_token_accuracy": 0.7687566743956672,
27
+ "num_tokens": 4791423.0,
28
+ "step": 10
29
+ },
30
+ {
31
+ "epoch": 1.7058823529411766,
32
+ "grad_norm": 0.6258080342354994,
33
+ "learning_rate": 2.8255813953488374e-05,
34
+ "loss": 0.881,
35
+ "mean_token_accuracy": 0.7985241502523422,
36
+ "num_tokens": 7330272.0,
37
+ "step": 15
38
+ },
39
+ {
40
+ "epoch": 2.235294117647059,
41
+ "grad_norm": 0.46238688658175153,
42
+ "learning_rate": 2.6511627906976747e-05,
43
+ "loss": 0.8499,
44
+ "mean_token_accuracy": 0.806600358751085,
45
+ "num_tokens": 9618952.0,
46
+ "step": 20
47
+ },
48
+ {
49
+ "epoch": 2.8235294117647056,
50
+ "grad_norm": 0.3244834177268814,
51
+ "learning_rate": 2.4767441860465116e-05,
52
+ "loss": 0.7258,
53
+ "mean_token_accuracy": 0.8285025209188461,
54
+ "num_tokens": 12114377.0,
55
+ "step": 25
56
+ },
57
+ {
58
+ "epoch": 3.3529411764705883,
59
+ "grad_norm": 0.3096128182615979,
60
+ "learning_rate": 2.302325581395349e-05,
61
+ "loss": 0.7092,
62
+ "mean_token_accuracy": 0.8342651062541537,
63
+ "num_tokens": 14409009.0,
64
+ "step": 30
65
+ },
66
+ {
67
+ "epoch": 3.9411764705882355,
68
+ "grad_norm": 1.5240607136739224,
69
+ "learning_rate": 2.1279069767441862e-05,
70
+ "loss": 0.64,
71
+ "mean_token_accuracy": 0.8458412200212478,
72
+ "num_tokens": 16918082.0,
73
+ "step": 35
74
+ },
75
+ {
76
+ "epoch": 4.470588235294118,
77
+ "grad_norm": 0.4386330787702683,
78
+ "learning_rate": 1.9534883720930235e-05,
79
+ "loss": 0.6372,
80
+ "mean_token_accuracy": 0.8506042758623759,
81
+ "num_tokens": 19217454.0,
82
+ "step": 40
83
+ },
84
+ {
85
+ "epoch": 5.0,
86
+ "grad_norm": 0.32130536815260163,
87
+ "learning_rate": 1.7790697674418608e-05,
88
+ "loss": 0.5271,
89
+ "mean_token_accuracy": 0.870173497332467,
90
+ "num_tokens": 21475135.0,
91
+ "step": 45
92
+ },
93
+ {
94
+ "epoch": 5.588235294117647,
95
+ "grad_norm": 0.38825023600544556,
96
+ "learning_rate": 1.6046511627906977e-05,
97
+ "loss": 0.533,
98
+ "mean_token_accuracy": 0.8699036419391633,
99
+ "num_tokens": 23999790.0,
100
+ "step": 50
101
+ },
102
+ {
103
+ "epoch": 6.117647058823529,
104
+ "grad_norm": 0.5588159986106253,
105
+ "learning_rate": 1.430232558139535e-05,
106
+ "loss": 0.4696,
107
+ "mean_token_accuracy": 0.886308984624015,
108
+ "num_tokens": 26264984.0,
109
+ "step": 55
110
+ },
111
+ {
112
+ "epoch": 6.705882352941177,
113
+ "grad_norm": 0.5373227236502689,
114
+ "learning_rate": 1.2558139534883723e-05,
115
+ "loss": 0.3877,
116
+ "mean_token_accuracy": 0.9013922065496445,
117
+ "num_tokens": 28792279.0,
118
+ "step": 60
119
+ },
120
+ {
121
+ "epoch": 7.235294117647059,
122
+ "grad_norm": 0.5457578900062939,
123
+ "learning_rate": 1.0813953488372092e-05,
124
+ "loss": 0.484,
125
+ "mean_token_accuracy": 0.8886518941985236,
126
+ "num_tokens": 31085796.0,
127
+ "step": 65
128
+ },
129
+ {
130
+ "epoch": 7.823529411764706,
131
+ "grad_norm": 0.5156132453867892,
132
+ "learning_rate": 9.069767441860465e-06,
133
+ "loss": 0.3649,
134
+ "mean_token_accuracy": 0.9116492509841919,
135
+ "num_tokens": 33579925.0,
136
+ "step": 70
137
+ },
138
+ {
139
+ "epoch": 8.352941176470589,
140
+ "grad_norm": 0.43157012641733306,
141
+ "learning_rate": 7.325581395348837e-06,
142
+ "loss": 0.3862,
143
+ "mean_token_accuracy": 0.9118325445387099,
144
+ "num_tokens": 35872214.0,
145
+ "step": 75
146
+ },
147
+ {
148
+ "epoch": 8.941176470588236,
149
+ "grad_norm": 0.39332288450299335,
150
+ "learning_rate": 5.581395348837209e-06,
151
+ "loss": 0.3342,
152
+ "mean_token_accuracy": 0.9180105596780777,
153
+ "num_tokens": 38392486.0,
154
+ "step": 80
155
+ },
156
+ {
157
+ "epoch": 9.470588235294118,
158
+ "grad_norm": 0.5517208078409448,
159
+ "learning_rate": 3.837209302325582e-06,
160
+ "loss": 0.3264,
161
+ "mean_token_accuracy": 0.9224550028642019,
162
+ "num_tokens": 40676022.0,
163
+ "step": 85
164
+ },
165
+ {
166
+ "epoch": 10.0,
167
+ "grad_norm": 0.6739351616750774,
168
+ "learning_rate": 2.0930232558139536e-06,
169
+ "loss": 0.3066,
170
+ "mean_token_accuracy": 0.9260480867491828,
171
+ "num_tokens": 42948208.0,
172
+ "step": 90
173
+ },
174
+ {
175
+ "epoch": 10.588235294117647,
176
+ "grad_norm": 0.35461902887245744,
177
+ "learning_rate": 3.4883720930232557e-07,
178
+ "loss": 0.3026,
179
+ "mean_token_accuracy": 0.9277766048908234,
180
+ "num_tokens": 45475525.0,
181
+ "step": 95
182
+ },
183
+ {
184
+ "epoch": 10.705882352941176,
185
+ "mean_token_accuracy": 0.9401646554470062,
186
+ "num_tokens": 45971032.0,
187
+ "step": 96,
188
+ "total_flos": 68866778333184.0,
189
+ "train_loss": 0.5774029536793629,
190
+ "train_runtime": 585.0314,
191
+ "train_samples_per_second": 11.056,
192
+ "train_steps_per_second": 0.164
193
+ }
194
+ ],
195
+ "logging_steps": 5,
196
+ "max_steps": 96,
197
+ "num_input_tokens_seen": 0,
198
+ "num_train_epochs": 12,
199
+ "save_steps": 500,
200
+ "stateful_callbacks": {
201
+ "TrainerControl": {
202
+ "args": {
203
+ "should_epoch_stop": false,
204
+ "should_evaluate": false,
205
+ "should_log": false,
206
+ "should_save": true,
207
+ "should_training_stop": true
208
+ },
209
+ "attributes": {}
210
+ }
211
+ },
212
+ "total_flos": 68866778333184.0,
213
+ "train_batch_size": 2,
214
+ "trial_name": null,
215
+ "trial_params": null
216
+ }