lucadang commited on
Commit
0cbe390
·
verified ·
1 Parent(s): 3cece86

Upload folder using huggingface_hub

Browse files
.gitattributes CHANGED
@@ -33,3 +33,4 @@ 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
+ tokenizer.json filter=lfs diff=lfs merge=lfs -text
added_tokens.json ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "</tool_call>": 151658,
3
+ "<tool_call>": 151657,
4
+ "<|box_end|>": 151649,
5
+ "<|box_start|>": 151648,
6
+ "<|endoftext|>": 151643,
7
+ "<|file_sep|>": 151664,
8
+ "<|fim_middle|>": 151660,
9
+ "<|fim_pad|>": 151662,
10
+ "<|fim_prefix|>": 151659,
11
+ "<|fim_suffix|>": 151661,
12
+ "<|im_end|>": 151645,
13
+ "<|im_start|>": 151644,
14
+ "<|image_pad|>": 151655,
15
+ "<|object_ref_end|>": 151647,
16
+ "<|object_ref_start|>": 151646,
17
+ "<|quad_end|>": 151651,
18
+ "<|quad_start|>": 151650,
19
+ "<|repo_name|>": 151663,
20
+ "<|video_pad|>": 151656,
21
+ "<|vision_end|>": 151653,
22
+ "<|vision_pad|>": 151654,
23
+ "<|vision_start|>": 151652
24
+ }
chat_template.jinja ADDED
@@ -0,0 +1,54 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {%- if tools %}
2
+ {{- '<|im_start|>system\n' }}
3
+ {%- if messages[0]['role'] == 'system' %}
4
+ {{- messages[0]['content'] }}
5
+ {%- else %}
6
+ {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
7
+ {%- endif %}
8
+ {{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
9
+ {%- for tool in tools %}
10
+ {{- "\n" }}
11
+ {{- tool | tojson }}
12
+ {%- endfor %}
13
+ {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
14
+ {%- else %}
15
+ {%- if messages[0]['role'] == 'system' %}
16
+ {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
17
+ {%- else %}
18
+ {{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
19
+ {%- endif %}
20
+ {%- endif %}
21
+ {%- for message in messages %}
22
+ {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
23
+ {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
24
+ {%- elif message.role == "assistant" %}
25
+ {{- '<|im_start|>' + message.role }}
26
+ {%- if message.content %}
27
+ {{- '\n' + message.content }}
28
+ {%- endif %}
29
+ {%- for tool_call in message.tool_calls %}
30
+ {%- if tool_call.function is defined %}
31
+ {%- set tool_call = tool_call.function %}
32
+ {%- endif %}
33
+ {{- '\n<tool_call>\n{"name": "' }}
34
+ {{- tool_call.name }}
35
+ {{- '", "arguments": ' }}
36
+ {{- tool_call.arguments | tojson }}
37
+ {{- '}\n</tool_call>' }}
38
+ {%- endfor %}
39
+ {{- '<|im_end|>\n' }}
40
+ {%- elif message.role == "tool" %}
41
+ {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
42
+ {{- '<|im_start|>user' }}
43
+ {%- endif %}
44
+ {{- '\n<tool_response>\n' }}
45
+ {{- message.content }}
46
+ {{- '\n</tool_response>' }}
47
+ {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
48
+ {{- '<|im_end|>\n' }}
49
+ {%- endif %}
50
+ {%- endif %}
51
+ {%- endfor %}
52
+ {%- if add_generation_prompt %}
53
+ {{- '<|im_start|>assistant\n' }}
54
+ {%- endif %}
config.json ADDED
@@ -0,0 +1,58 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "architectures": [
3
+ "Qwen2ForCausalLM"
4
+ ],
5
+ "attention_dropout": 0.0,
6
+ "bos_token_id": 151643,
7
+ "eos_token_id": 151645,
8
+ "hidden_act": "silu",
9
+ "hidden_size": 3584,
10
+ "initializer_range": 0.02,
11
+ "intermediate_size": 18944,
12
+ "layer_types": [
13
+ "full_attention",
14
+ "full_attention",
15
+ "full_attention",
16
+ "full_attention",
17
+ "full_attention",
18
+ "full_attention",
19
+ "full_attention",
20
+ "full_attention",
21
+ "full_attention",
22
+ "full_attention",
23
+ "full_attention",
24
+ "full_attention",
25
+ "full_attention",
26
+ "full_attention",
27
+ "full_attention",
28
+ "full_attention",
29
+ "full_attention",
30
+ "full_attention",
31
+ "full_attention",
32
+ "full_attention",
33
+ "full_attention",
34
+ "full_attention",
35
+ "full_attention",
36
+ "full_attention",
37
+ "full_attention",
38
+ "full_attention",
39
+ "full_attention",
40
+ "full_attention"
41
+ ],
42
+ "max_position_embeddings": 32768,
43
+ "max_window_layers": 28,
44
+ "model_type": "qwen2",
45
+ "num_attention_heads": 28,
46
+ "num_hidden_layers": 28,
47
+ "num_key_value_heads": 4,
48
+ "rms_norm_eps": 1e-06,
49
+ "rope_scaling": null,
50
+ "rope_theta": 1000000.0,
51
+ "sliding_window": null,
52
+ "tie_word_embeddings": false,
53
+ "torch_dtype": "bfloat16",
54
+ "transformers_version": "4.53.1",
55
+ "use_cache": false,
56
+ "use_sliding_window": false,
57
+ "vocab_size": 152064
58
+ }
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": "4.53.1"
14
+ }
merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
model-00001-of-00004.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0666227de48831c3ef925ace4a287f6078944d319523555e6db8513a86298e75
3
+ size 4877660776
model-00002-of-00004.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:2cc9b76d4aa974cfd8c20c1be5111a164299d93246b00ca6f0885be8f85c0296
3
+ size 4932751008
model-00003-of-00004.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:2ee032124f263d373c65b3d8e6f05fb03cc59aa02b54f44989f912750b6426d0
3
+ size 4330865200
model-00004-of-00004.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e09bccfa9a85756b9279c91c785b72904f52bdbc56e7d1d8796eda43d31b16a3
3
+ size 1089994880
model.safetensors.index.json ADDED
@@ -0,0 +1,347 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "metadata": {
3
+ "total_parameters": 333312,
4
+ "total_size": 15231233024
5
+ },
6
+ "weight_map": {
7
+ "lm_head.weight": "model-00004-of-00004.safetensors",
8
+ "model.embed_tokens.weight": "model-00001-of-00004.safetensors",
9
+ "model.layers.0.input_layernorm.weight": "model-00001-of-00004.safetensors",
10
+ "model.layers.0.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
11
+ "model.layers.0.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
12
+ "model.layers.0.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
13
+ "model.layers.0.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
14
+ "model.layers.0.self_attn.k_proj.bias": "model-00001-of-00004.safetensors",
15
+ "model.layers.0.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
16
+ "model.layers.0.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
17
+ "model.layers.0.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
18
+ "model.layers.0.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
19
+ "model.layers.0.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
20
+ "model.layers.0.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
21
+ "model.layers.1.input_layernorm.weight": "model-00001-of-00004.safetensors",
22
+ "model.layers.1.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
23
+ "model.layers.1.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
24
+ "model.layers.1.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
25
+ "model.layers.1.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
26
+ "model.layers.1.self_attn.k_proj.bias": "model-00001-of-00004.safetensors",
27
+ "model.layers.1.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
28
+ "model.layers.1.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
29
+ "model.layers.1.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
30
+ "model.layers.1.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
31
+ "model.layers.1.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
32
+ "model.layers.1.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
33
+ "model.layers.10.input_layernorm.weight": "model-00002-of-00004.safetensors",
34
+ "model.layers.10.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
35
+ "model.layers.10.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
36
+ "model.layers.10.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
37
+ "model.layers.10.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
38
+ "model.layers.10.self_attn.k_proj.bias": "model-00002-of-00004.safetensors",
39
+ "model.layers.10.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
40
+ "model.layers.10.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
41
+ "model.layers.10.self_attn.q_proj.bias": "model-00002-of-00004.safetensors",
42
+ "model.layers.10.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
43
+ "model.layers.10.self_attn.v_proj.bias": "model-00002-of-00004.safetensors",
44
+ "model.layers.10.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
45
+ "model.layers.11.input_layernorm.weight": "model-00002-of-00004.safetensors",
46
+ "model.layers.11.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
47
+ "model.layers.11.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
48
+ "model.layers.11.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
49
+ "model.layers.11.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
50
+ "model.layers.11.self_attn.k_proj.bias": "model-00002-of-00004.safetensors",
51
+ "model.layers.11.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
52
+ "model.layers.11.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
53
+ "model.layers.11.self_attn.q_proj.bias": "model-00002-of-00004.safetensors",
54
+ "model.layers.11.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
55
+ "model.layers.11.self_attn.v_proj.bias": "model-00002-of-00004.safetensors",
56
+ "model.layers.11.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
57
+ "model.layers.12.input_layernorm.weight": "model-00002-of-00004.safetensors",
58
+ "model.layers.12.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
59
+ "model.layers.12.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
60
+ "model.layers.12.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
61
+ "model.layers.12.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
62
+ "model.layers.12.self_attn.k_proj.bias": "model-00002-of-00004.safetensors",
63
+ "model.layers.12.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
64
+ "model.layers.12.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
65
+ "model.layers.12.self_attn.q_proj.bias": "model-00002-of-00004.safetensors",
66
+ "model.layers.12.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
67
+ "model.layers.12.self_attn.v_proj.bias": "model-00002-of-00004.safetensors",
68
+ "model.layers.12.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
69
+ "model.layers.13.input_layernorm.weight": "model-00002-of-00004.safetensors",
70
+ "model.layers.13.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
71
+ "model.layers.13.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
72
+ "model.layers.13.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
73
+ "model.layers.13.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
74
+ "model.layers.13.self_attn.k_proj.bias": "model-00002-of-00004.safetensors",
75
+ "model.layers.13.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
76
+ "model.layers.13.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
77
+ "model.layers.13.self_attn.q_proj.bias": "model-00002-of-00004.safetensors",
78
+ "model.layers.13.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
79
+ "model.layers.13.self_attn.v_proj.bias": "model-00002-of-00004.safetensors",
80
+ "model.layers.13.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
81
+ "model.layers.14.input_layernorm.weight": "model-00002-of-00004.safetensors",
82
+ "model.layers.14.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
83
+ "model.layers.14.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
84
+ "model.layers.14.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
85
+ "model.layers.14.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
86
+ "model.layers.14.self_attn.k_proj.bias": "model-00002-of-00004.safetensors",
87
+ "model.layers.14.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
88
+ "model.layers.14.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
89
+ "model.layers.14.self_attn.q_proj.bias": "model-00002-of-00004.safetensors",
90
+ "model.layers.14.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
91
+ "model.layers.14.self_attn.v_proj.bias": "model-00002-of-00004.safetensors",
92
+ "model.layers.14.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
93
+ "model.layers.15.input_layernorm.weight": "model-00002-of-00004.safetensors",
94
+ "model.layers.15.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
95
+ "model.layers.15.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
96
+ "model.layers.15.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
97
+ "model.layers.15.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
98
+ "model.layers.15.self_attn.k_proj.bias": "model-00002-of-00004.safetensors",
99
+ "model.layers.15.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
100
+ "model.layers.15.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
101
+ "model.layers.15.self_attn.q_proj.bias": "model-00002-of-00004.safetensors",
102
+ "model.layers.15.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
103
+ "model.layers.15.self_attn.v_proj.bias": "model-00002-of-00004.safetensors",
104
+ "model.layers.15.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
105
+ "model.layers.16.input_layernorm.weight": "model-00002-of-00004.safetensors",
106
+ "model.layers.16.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
107
+ "model.layers.16.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
108
+ "model.layers.16.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
109
+ "model.layers.16.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
110
+ "model.layers.16.self_attn.k_proj.bias": "model-00002-of-00004.safetensors",
111
+ "model.layers.16.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
112
+ "model.layers.16.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
113
+ "model.layers.16.self_attn.q_proj.bias": "model-00002-of-00004.safetensors",
114
+ "model.layers.16.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
115
+ "model.layers.16.self_attn.v_proj.bias": "model-00002-of-00004.safetensors",
116
+ "model.layers.16.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
117
+ "model.layers.17.input_layernorm.weight": "model-00002-of-00004.safetensors",
118
+ "model.layers.17.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
119
+ "model.layers.17.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
120
+ "model.layers.17.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
121
+ "model.layers.17.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
122
+ "model.layers.17.self_attn.k_proj.bias": "model-00002-of-00004.safetensors",
123
+ "model.layers.17.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
124
+ "model.layers.17.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
125
+ "model.layers.17.self_attn.q_proj.bias": "model-00002-of-00004.safetensors",
126
+ "model.layers.17.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
127
+ "model.layers.17.self_attn.v_proj.bias": "model-00002-of-00004.safetensors",
128
+ "model.layers.17.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
129
+ "model.layers.18.input_layernorm.weight": "model-00003-of-00004.safetensors",
130
+ "model.layers.18.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
131
+ "model.layers.18.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
132
+ "model.layers.18.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
133
+ "model.layers.18.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
134
+ "model.layers.18.self_attn.k_proj.bias": "model-00002-of-00004.safetensors",
135
+ "model.layers.18.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
136
+ "model.layers.18.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
137
+ "model.layers.18.self_attn.q_proj.bias": "model-00002-of-00004.safetensors",
138
+ "model.layers.18.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
139
+ "model.layers.18.self_attn.v_proj.bias": "model-00002-of-00004.safetensors",
140
+ "model.layers.18.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
141
+ "model.layers.19.input_layernorm.weight": "model-00003-of-00004.safetensors",
142
+ "model.layers.19.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
143
+ "model.layers.19.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
144
+ "model.layers.19.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
145
+ "model.layers.19.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
146
+ "model.layers.19.self_attn.k_proj.bias": "model-00003-of-00004.safetensors",
147
+ "model.layers.19.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
148
+ "model.layers.19.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
149
+ "model.layers.19.self_attn.q_proj.bias": "model-00003-of-00004.safetensors",
150
+ "model.layers.19.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
151
+ "model.layers.19.self_attn.v_proj.bias": "model-00003-of-00004.safetensors",
152
+ "model.layers.19.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
153
+ "model.layers.2.input_layernorm.weight": "model-00001-of-00004.safetensors",
154
+ "model.layers.2.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
155
+ "model.layers.2.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
156
+ "model.layers.2.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
157
+ "model.layers.2.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
158
+ "model.layers.2.self_attn.k_proj.bias": "model-00001-of-00004.safetensors",
159
+ "model.layers.2.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
160
+ "model.layers.2.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
161
+ "model.layers.2.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
162
+ "model.layers.2.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
163
+ "model.layers.2.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
164
+ "model.layers.2.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
165
+ "model.layers.20.input_layernorm.weight": "model-00003-of-00004.safetensors",
166
+ "model.layers.20.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
167
+ "model.layers.20.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
168
+ "model.layers.20.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
169
+ "model.layers.20.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
170
+ "model.layers.20.self_attn.k_proj.bias": "model-00003-of-00004.safetensors",
171
+ "model.layers.20.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
172
+ "model.layers.20.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
173
+ "model.layers.20.self_attn.q_proj.bias": "model-00003-of-00004.safetensors",
174
+ "model.layers.20.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
175
+ "model.layers.20.self_attn.v_proj.bias": "model-00003-of-00004.safetensors",
176
+ "model.layers.20.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
177
+ "model.layers.21.input_layernorm.weight": "model-00003-of-00004.safetensors",
178
+ "model.layers.21.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
179
+ "model.layers.21.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
180
+ "model.layers.21.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
181
+ "model.layers.21.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
182
+ "model.layers.21.self_attn.k_proj.bias": "model-00003-of-00004.safetensors",
183
+ "model.layers.21.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
184
+ "model.layers.21.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
185
+ "model.layers.21.self_attn.q_proj.bias": "model-00003-of-00004.safetensors",
186
+ "model.layers.21.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
187
+ "model.layers.21.self_attn.v_proj.bias": "model-00003-of-00004.safetensors",
188
+ "model.layers.21.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
189
+ "model.layers.22.input_layernorm.weight": "model-00003-of-00004.safetensors",
190
+ "model.layers.22.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
191
+ "model.layers.22.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
192
+ "model.layers.22.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
193
+ "model.layers.22.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
194
+ "model.layers.22.self_attn.k_proj.bias": "model-00003-of-00004.safetensors",
195
+ "model.layers.22.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
196
+ "model.layers.22.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
197
+ "model.layers.22.self_attn.q_proj.bias": "model-00003-of-00004.safetensors",
198
+ "model.layers.22.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
199
+ "model.layers.22.self_attn.v_proj.bias": "model-00003-of-00004.safetensors",
200
+ "model.layers.22.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
201
+ "model.layers.23.input_layernorm.weight": "model-00003-of-00004.safetensors",
202
+ "model.layers.23.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
203
+ "model.layers.23.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
204
+ "model.layers.23.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
205
+ "model.layers.23.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
206
+ "model.layers.23.self_attn.k_proj.bias": "model-00003-of-00004.safetensors",
207
+ "model.layers.23.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
208
+ "model.layers.23.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
209
+ "model.layers.23.self_attn.q_proj.bias": "model-00003-of-00004.safetensors",
210
+ "model.layers.23.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
211
+ "model.layers.23.self_attn.v_proj.bias": "model-00003-of-00004.safetensors",
212
+ "model.layers.23.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
213
+ "model.layers.24.input_layernorm.weight": "model-00003-of-00004.safetensors",
214
+ "model.layers.24.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
215
+ "model.layers.24.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
216
+ "model.layers.24.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
217
+ "model.layers.24.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
218
+ "model.layers.24.self_attn.k_proj.bias": "model-00003-of-00004.safetensors",
219
+ "model.layers.24.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
220
+ "model.layers.24.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
221
+ "model.layers.24.self_attn.q_proj.bias": "model-00003-of-00004.safetensors",
222
+ "model.layers.24.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
223
+ "model.layers.24.self_attn.v_proj.bias": "model-00003-of-00004.safetensors",
224
+ "model.layers.24.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
225
+ "model.layers.25.input_layernorm.weight": "model-00003-of-00004.safetensors",
226
+ "model.layers.25.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
227
+ "model.layers.25.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
228
+ "model.layers.25.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
229
+ "model.layers.25.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
230
+ "model.layers.25.self_attn.k_proj.bias": "model-00003-of-00004.safetensors",
231
+ "model.layers.25.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
232
+ "model.layers.25.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
233
+ "model.layers.25.self_attn.q_proj.bias": "model-00003-of-00004.safetensors",
234
+ "model.layers.25.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
235
+ "model.layers.25.self_attn.v_proj.bias": "model-00003-of-00004.safetensors",
236
+ "model.layers.25.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
237
+ "model.layers.26.input_layernorm.weight": "model-00003-of-00004.safetensors",
238
+ "model.layers.26.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
239
+ "model.layers.26.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
240
+ "model.layers.26.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
241
+ "model.layers.26.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
242
+ "model.layers.26.self_attn.k_proj.bias": "model-00003-of-00004.safetensors",
243
+ "model.layers.26.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
244
+ "model.layers.26.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
245
+ "model.layers.26.self_attn.q_proj.bias": "model-00003-of-00004.safetensors",
246
+ "model.layers.26.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
247
+ "model.layers.26.self_attn.v_proj.bias": "model-00003-of-00004.safetensors",
248
+ "model.layers.26.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
249
+ "model.layers.27.input_layernorm.weight": "model-00003-of-00004.safetensors",
250
+ "model.layers.27.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
251
+ "model.layers.27.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
252
+ "model.layers.27.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
253
+ "model.layers.27.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
254
+ "model.layers.27.self_attn.k_proj.bias": "model-00003-of-00004.safetensors",
255
+ "model.layers.27.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
256
+ "model.layers.27.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
257
+ "model.layers.27.self_attn.q_proj.bias": "model-00003-of-00004.safetensors",
258
+ "model.layers.27.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
259
+ "model.layers.27.self_attn.v_proj.bias": "model-00003-of-00004.safetensors",
260
+ "model.layers.27.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
261
+ "model.layers.3.input_layernorm.weight": "model-00001-of-00004.safetensors",
262
+ "model.layers.3.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
263
+ "model.layers.3.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
264
+ "model.layers.3.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
265
+ "model.layers.3.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
266
+ "model.layers.3.self_attn.k_proj.bias": "model-00001-of-00004.safetensors",
267
+ "model.layers.3.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
268
+ "model.layers.3.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
269
+ "model.layers.3.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
270
+ "model.layers.3.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
271
+ "model.layers.3.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
272
+ "model.layers.3.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
273
+ "model.layers.4.input_layernorm.weight": "model-00001-of-00004.safetensors",
274
+ "model.layers.4.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
275
+ "model.layers.4.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
276
+ "model.layers.4.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
277
+ "model.layers.4.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
278
+ "model.layers.4.self_attn.k_proj.bias": "model-00001-of-00004.safetensors",
279
+ "model.layers.4.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
280
+ "model.layers.4.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
281
+ "model.layers.4.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
282
+ "model.layers.4.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
283
+ "model.layers.4.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
284
+ "model.layers.4.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
285
+ "model.layers.5.input_layernorm.weight": "model-00001-of-00004.safetensors",
286
+ "model.layers.5.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
287
+ "model.layers.5.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
288
+ "model.layers.5.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
289
+ "model.layers.5.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
290
+ "model.layers.5.self_attn.k_proj.bias": "model-00001-of-00004.safetensors",
291
+ "model.layers.5.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
292
+ "model.layers.5.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
293
+ "model.layers.5.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
294
+ "model.layers.5.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
295
+ "model.layers.5.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
296
+ "model.layers.5.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
297
+ "model.layers.6.input_layernorm.weight": "model-00001-of-00004.safetensors",
298
+ "model.layers.6.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
299
+ "model.layers.6.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
300
+ "model.layers.6.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
301
+ "model.layers.6.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
302
+ "model.layers.6.self_attn.k_proj.bias": "model-00001-of-00004.safetensors",
303
+ "model.layers.6.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
304
+ "model.layers.6.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
305
+ "model.layers.6.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
306
+ "model.layers.6.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
307
+ "model.layers.6.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
308
+ "model.layers.6.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
309
+ "model.layers.7.input_layernorm.weight": "model-00001-of-00004.safetensors",
310
+ "model.layers.7.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
311
+ "model.layers.7.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
312
+ "model.layers.7.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
313
+ "model.layers.7.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
314
+ "model.layers.7.self_attn.k_proj.bias": "model-00001-of-00004.safetensors",
315
+ "model.layers.7.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
316
+ "model.layers.7.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
317
+ "model.layers.7.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
318
+ "model.layers.7.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
319
+ "model.layers.7.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
320
+ "model.layers.7.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
321
+ "model.layers.8.input_layernorm.weight": "model-00002-of-00004.safetensors",
322
+ "model.layers.8.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
323
+ "model.layers.8.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
324
+ "model.layers.8.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
325
+ "model.layers.8.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
326
+ "model.layers.8.self_attn.k_proj.bias": "model-00001-of-00004.safetensors",
327
+ "model.layers.8.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
328
+ "model.layers.8.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
329
+ "model.layers.8.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
330
+ "model.layers.8.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
331
+ "model.layers.8.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
332
+ "model.layers.8.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
333
+ "model.layers.9.input_layernorm.weight": "model-00002-of-00004.safetensors",
334
+ "model.layers.9.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
335
+ "model.layers.9.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
336
+ "model.layers.9.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
337
+ "model.layers.9.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
338
+ "model.layers.9.self_attn.k_proj.bias": "model-00002-of-00004.safetensors",
339
+ "model.layers.9.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
340
+ "model.layers.9.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
341
+ "model.layers.9.self_attn.q_proj.bias": "model-00002-of-00004.safetensors",
342
+ "model.layers.9.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
343
+ "model.layers.9.self_attn.v_proj.bias": "model-00002-of-00004.safetensors",
344
+ "model.layers.9.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
345
+ "model.norm.weight": "model-00003-of-00004.safetensors"
346
+ }
347
+ }
special_tokens_map.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "additional_special_tokens": [
3
+ "<|im_start|>",
4
+ "<|im_end|>",
5
+ "<|object_ref_start|>",
6
+ "<|object_ref_end|>",
7
+ "<|box_start|>",
8
+ "<|box_end|>",
9
+ "<|quad_start|>",
10
+ "<|quad_end|>",
11
+ "<|vision_start|>",
12
+ "<|vision_end|>",
13
+ "<|vision_pad|>",
14
+ "<|image_pad|>",
15
+ "<|video_pad|>"
16
+ ],
17
+ "eos_token": {
18
+ "content": "<|im_end|>",
19
+ "lstrip": false,
20
+ "normalized": false,
21
+ "rstrip": false,
22
+ "single_word": false
23
+ },
24
+ "pad_token": {
25
+ "content": "<|endoftext|>",
26
+ "lstrip": false,
27
+ "normalized": false,
28
+ "rstrip": false,
29
+ "single_word": false
30
+ }
31
+ }
tokenizer.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9c5ae00e602b8860cbd784ba82a8aa14e8feecec692e7076590d014d7b7fdafa
3
+ size 11421896
tokenizer_config.json ADDED
@@ -0,0 +1,207 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": false,
3
+ "add_prefix_space": false,
4
+ "added_tokens_decoder": {
5
+ "151643": {
6
+ "content": "<|endoftext|>",
7
+ "lstrip": false,
8
+ "normalized": false,
9
+ "rstrip": false,
10
+ "single_word": false,
11
+ "special": true
12
+ },
13
+ "151644": {
14
+ "content": "<|im_start|>",
15
+ "lstrip": false,
16
+ "normalized": false,
17
+ "rstrip": false,
18
+ "single_word": false,
19
+ "special": true
20
+ },
21
+ "151645": {
22
+ "content": "<|im_end|>",
23
+ "lstrip": false,
24
+ "normalized": false,
25
+ "rstrip": false,
26
+ "single_word": false,
27
+ "special": true
28
+ },
29
+ "151646": {
30
+ "content": "<|object_ref_start|>",
31
+ "lstrip": false,
32
+ "normalized": false,
33
+ "rstrip": false,
34
+ "single_word": false,
35
+ "special": true
36
+ },
37
+ "151647": {
38
+ "content": "<|object_ref_end|>",
39
+ "lstrip": false,
40
+ "normalized": false,
41
+ "rstrip": false,
42
+ "single_word": false,
43
+ "special": true
44
+ },
45
+ "151648": {
46
+ "content": "<|box_start|>",
47
+ "lstrip": false,
48
+ "normalized": false,
49
+ "rstrip": false,
50
+ "single_word": false,
51
+ "special": true
52
+ },
53
+ "151649": {
54
+ "content": "<|box_end|>",
55
+ "lstrip": false,
56
+ "normalized": false,
57
+ "rstrip": false,
58
+ "single_word": false,
59
+ "special": true
60
+ },
61
+ "151650": {
62
+ "content": "<|quad_start|>",
63
+ "lstrip": false,
64
+ "normalized": false,
65
+ "rstrip": false,
66
+ "single_word": false,
67
+ "special": true
68
+ },
69
+ "151651": {
70
+ "content": "<|quad_end|>",
71
+ "lstrip": false,
72
+ "normalized": false,
73
+ "rstrip": false,
74
+ "single_word": false,
75
+ "special": true
76
+ },
77
+ "151652": {
78
+ "content": "<|vision_start|>",
79
+ "lstrip": false,
80
+ "normalized": false,
81
+ "rstrip": false,
82
+ "single_word": false,
83
+ "special": true
84
+ },
85
+ "151653": {
86
+ "content": "<|vision_end|>",
87
+ "lstrip": false,
88
+ "normalized": false,
89
+ "rstrip": false,
90
+ "single_word": false,
91
+ "special": true
92
+ },
93
+ "151654": {
94
+ "content": "<|vision_pad|>",
95
+ "lstrip": false,
96
+ "normalized": false,
97
+ "rstrip": false,
98
+ "single_word": false,
99
+ "special": true
100
+ },
101
+ "151655": {
102
+ "content": "<|image_pad|>",
103
+ "lstrip": false,
104
+ "normalized": false,
105
+ "rstrip": false,
106
+ "single_word": false,
107
+ "special": true
108
+ },
109
+ "151656": {
110
+ "content": "<|video_pad|>",
111
+ "lstrip": false,
112
+ "normalized": false,
113
+ "rstrip": false,
114
+ "single_word": false,
115
+ "special": true
116
+ },
117
+ "151657": {
118
+ "content": "<tool_call>",
119
+ "lstrip": false,
120
+ "normalized": false,
121
+ "rstrip": false,
122
+ "single_word": false,
123
+ "special": false
124
+ },
125
+ "151658": {
126
+ "content": "</tool_call>",
127
+ "lstrip": false,
128
+ "normalized": false,
129
+ "rstrip": false,
130
+ "single_word": false,
131
+ "special": false
132
+ },
133
+ "151659": {
134
+ "content": "<|fim_prefix|>",
135
+ "lstrip": false,
136
+ "normalized": false,
137
+ "rstrip": false,
138
+ "single_word": false,
139
+ "special": false
140
+ },
141
+ "151660": {
142
+ "content": "<|fim_middle|>",
143
+ "lstrip": false,
144
+ "normalized": false,
145
+ "rstrip": false,
146
+ "single_word": false,
147
+ "special": false
148
+ },
149
+ "151661": {
150
+ "content": "<|fim_suffix|>",
151
+ "lstrip": false,
152
+ "normalized": false,
153
+ "rstrip": false,
154
+ "single_word": false,
155
+ "special": false
156
+ },
157
+ "151662": {
158
+ "content": "<|fim_pad|>",
159
+ "lstrip": false,
160
+ "normalized": false,
161
+ "rstrip": false,
162
+ "single_word": false,
163
+ "special": false
164
+ },
165
+ "151663": {
166
+ "content": "<|repo_name|>",
167
+ "lstrip": false,
168
+ "normalized": false,
169
+ "rstrip": false,
170
+ "single_word": false,
171
+ "special": false
172
+ },
173
+ "151664": {
174
+ "content": "<|file_sep|>",
175
+ "lstrip": false,
176
+ "normalized": false,
177
+ "rstrip": false,
178
+ "single_word": false,
179
+ "special": false
180
+ }
181
+ },
182
+ "additional_special_tokens": [
183
+ "<|im_start|>",
184
+ "<|im_end|>",
185
+ "<|object_ref_start|>",
186
+ "<|object_ref_end|>",
187
+ "<|box_start|>",
188
+ "<|box_end|>",
189
+ "<|quad_start|>",
190
+ "<|quad_end|>",
191
+ "<|vision_start|>",
192
+ "<|vision_end|>",
193
+ "<|vision_pad|>",
194
+ "<|image_pad|>",
195
+ "<|video_pad|>"
196
+ ],
197
+ "bos_token": null,
198
+ "clean_up_tokenization_spaces": false,
199
+ "eos_token": "<|im_end|>",
200
+ "errors": "replace",
201
+ "extra_special_tokens": {},
202
+ "model_max_length": 131072,
203
+ "pad_token": "<|endoftext|>",
204
+ "split_special_tokens": false,
205
+ "tokenizer_class": "Qwen2Tokenizer",
206
+ "unk_token": null
207
+ }
trainer_state.json ADDED
@@ -0,0 +1,1654 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_global_step": null,
3
+ "best_metric": null,
4
+ "best_model_checkpoint": null,
5
+ "epoch": 3.0,
6
+ "eval_steps": 500,
7
+ "global_step": 180,
8
+ "is_hyper_param_search": false,
9
+ "is_local_process_zero": true,
10
+ "is_world_process_zero": true,
11
+ "log_history": [
12
+ {
13
+ "epoch": 0.016666666666666666,
14
+ "grad_norm": 10.415586015798965,
15
+ "learning_rate": 2e-05,
16
+ "loss": 0.3928,
17
+ "mean_token_accuracy": 0.8857417702674866,
18
+ "num_tokens": 20323.0,
19
+ "step": 1
20
+ },
21
+ {
22
+ "epoch": 0.03333333333333333,
23
+ "grad_norm": 10.271130520144448,
24
+ "learning_rate": 1.988888888888889e-05,
25
+ "loss": 0.4512,
26
+ "mean_token_accuracy": 0.8707664608955383,
27
+ "num_tokens": 38981.0,
28
+ "step": 2
29
+ },
30
+ {
31
+ "epoch": 0.05,
32
+ "grad_norm": 8.880344134520183,
33
+ "learning_rate": 1.977777777777778e-05,
34
+ "loss": 0.4737,
35
+ "mean_token_accuracy": 0.8786681890487671,
36
+ "num_tokens": 57347.0,
37
+ "step": 3
38
+ },
39
+ {
40
+ "epoch": 0.06666666666666667,
41
+ "grad_norm": 10.667150634660754,
42
+ "learning_rate": 1.9666666666666666e-05,
43
+ "loss": 0.3142,
44
+ "mean_token_accuracy": 0.9128794074058533,
45
+ "num_tokens": 76506.0,
46
+ "step": 4
47
+ },
48
+ {
49
+ "epoch": 0.08333333333333333,
50
+ "grad_norm": 8.532819211594981,
51
+ "learning_rate": 1.9555555555555557e-05,
52
+ "loss": 0.4014,
53
+ "mean_token_accuracy": 0.8839911222457886,
54
+ "num_tokens": 94986.0,
55
+ "step": 5
56
+ },
57
+ {
58
+ "epoch": 0.1,
59
+ "grad_norm": 8.472325495649157,
60
+ "learning_rate": 1.9444444444444445e-05,
61
+ "loss": 0.2534,
62
+ "mean_token_accuracy": 0.9193734526634216,
63
+ "num_tokens": 115823.0,
64
+ "step": 6
65
+ },
66
+ {
67
+ "epoch": 0.11666666666666667,
68
+ "grad_norm": 2.303889693461022,
69
+ "learning_rate": 1.9333333333333333e-05,
70
+ "loss": 0.2326,
71
+ "mean_token_accuracy": 0.9243853688240051,
72
+ "num_tokens": 135340.0,
73
+ "step": 7
74
+ },
75
+ {
76
+ "epoch": 0.13333333333333333,
77
+ "grad_norm": 1.9328717095833254,
78
+ "learning_rate": 1.9222222222222225e-05,
79
+ "loss": 0.2245,
80
+ "mean_token_accuracy": 0.9283159375190735,
81
+ "num_tokens": 155370.0,
82
+ "step": 8
83
+ },
84
+ {
85
+ "epoch": 0.15,
86
+ "grad_norm": 2.822202555840132,
87
+ "learning_rate": 1.9111111111111113e-05,
88
+ "loss": 0.2806,
89
+ "mean_token_accuracy": 0.9093520045280457,
90
+ "num_tokens": 174000.0,
91
+ "step": 9
92
+ },
93
+ {
94
+ "epoch": 0.16666666666666666,
95
+ "grad_norm": 1.5523434880416322,
96
+ "learning_rate": 1.9e-05,
97
+ "loss": 0.1998,
98
+ "mean_token_accuracy": 0.935231626033783,
99
+ "num_tokens": 195628.0,
100
+ "step": 10
101
+ },
102
+ {
103
+ "epoch": 0.18333333333333332,
104
+ "grad_norm": 2.4495550719902126,
105
+ "learning_rate": 1.888888888888889e-05,
106
+ "loss": 0.2645,
107
+ "mean_token_accuracy": 0.9143708944320679,
108
+ "num_tokens": 215718.0,
109
+ "step": 11
110
+ },
111
+ {
112
+ "epoch": 0.2,
113
+ "grad_norm": 2.271447813557674,
114
+ "learning_rate": 1.877777777777778e-05,
115
+ "loss": 0.2667,
116
+ "mean_token_accuracy": 0.912392795085907,
117
+ "num_tokens": 234724.0,
118
+ "step": 12
119
+ },
120
+ {
121
+ "epoch": 0.21666666666666667,
122
+ "grad_norm": 2.646542053112607,
123
+ "learning_rate": 1.866666666666667e-05,
124
+ "loss": 0.287,
125
+ "mean_token_accuracy": 0.9045044779777527,
126
+ "num_tokens": 253330.0,
127
+ "step": 13
128
+ },
129
+ {
130
+ "epoch": 0.23333333333333334,
131
+ "grad_norm": 2.170153048479742,
132
+ "learning_rate": 1.8555555555555557e-05,
133
+ "loss": 0.2268,
134
+ "mean_token_accuracy": 0.9230367541313171,
135
+ "num_tokens": 272130.0,
136
+ "step": 14
137
+ },
138
+ {
139
+ "epoch": 0.25,
140
+ "grad_norm": 1.8508062583233198,
141
+ "learning_rate": 1.8444444444444448e-05,
142
+ "loss": 0.2228,
143
+ "mean_token_accuracy": 0.9244704246520996,
144
+ "num_tokens": 292020.0,
145
+ "step": 15
146
+ },
147
+ {
148
+ "epoch": 0.26666666666666666,
149
+ "grad_norm": 1.8770429443477359,
150
+ "learning_rate": 1.8333333333333333e-05,
151
+ "loss": 0.236,
152
+ "mean_token_accuracy": 0.9211986660957336,
153
+ "num_tokens": 311379.0,
154
+ "step": 16
155
+ },
156
+ {
157
+ "epoch": 0.2833333333333333,
158
+ "grad_norm": 1.9148567988930494,
159
+ "learning_rate": 1.8222222222222224e-05,
160
+ "loss": 0.2231,
161
+ "mean_token_accuracy": 0.9292123913764954,
162
+ "num_tokens": 330451.0,
163
+ "step": 17
164
+ },
165
+ {
166
+ "epoch": 0.3,
167
+ "grad_norm": 1.612193810374408,
168
+ "learning_rate": 1.8111111111111112e-05,
169
+ "loss": 0.2204,
170
+ "mean_token_accuracy": 0.9254255294799805,
171
+ "num_tokens": 349197.0,
172
+ "step": 18
173
+ },
174
+ {
175
+ "epoch": 0.31666666666666665,
176
+ "grad_norm": 1.833360520767258,
177
+ "learning_rate": 1.8e-05,
178
+ "loss": 0.255,
179
+ "mean_token_accuracy": 0.9199110269546509,
180
+ "num_tokens": 369434.0,
181
+ "step": 19
182
+ },
183
+ {
184
+ "epoch": 0.3333333333333333,
185
+ "grad_norm": 1.89838266117527,
186
+ "learning_rate": 1.7888888888888892e-05,
187
+ "loss": 0.2617,
188
+ "mean_token_accuracy": 0.9107837080955505,
189
+ "num_tokens": 387390.0,
190
+ "step": 20
191
+ },
192
+ {
193
+ "epoch": 0.35,
194
+ "grad_norm": 1.689532449309742,
195
+ "learning_rate": 1.7777777777777777e-05,
196
+ "loss": 0.2406,
197
+ "mean_token_accuracy": 0.9206206202507019,
198
+ "num_tokens": 405986.0,
199
+ "step": 21
200
+ },
201
+ {
202
+ "epoch": 0.36666666666666664,
203
+ "grad_norm": 1.6883639816680873,
204
+ "learning_rate": 1.7666666666666668e-05,
205
+ "loss": 0.2468,
206
+ "mean_token_accuracy": 0.9216131567955017,
207
+ "num_tokens": 424773.0,
208
+ "step": 22
209
+ },
210
+ {
211
+ "epoch": 0.38333333333333336,
212
+ "grad_norm": 1.4657652178099831,
213
+ "learning_rate": 1.7555555555555556e-05,
214
+ "loss": 0.211,
215
+ "mean_token_accuracy": 0.9315024018287659,
216
+ "num_tokens": 444011.0,
217
+ "step": 23
218
+ },
219
+ {
220
+ "epoch": 0.4,
221
+ "grad_norm": 1.2496844817803525,
222
+ "learning_rate": 1.7444444444444448e-05,
223
+ "loss": 0.1853,
224
+ "mean_token_accuracy": 0.9384945631027222,
225
+ "num_tokens": 464975.0,
226
+ "step": 24
227
+ },
228
+ {
229
+ "epoch": 0.4166666666666667,
230
+ "grad_norm": 1.358446086201356,
231
+ "learning_rate": 1.7333333333333336e-05,
232
+ "loss": 0.198,
233
+ "mean_token_accuracy": 0.9333889484405518,
234
+ "num_tokens": 486425.0,
235
+ "step": 25
236
+ },
237
+ {
238
+ "epoch": 0.43333333333333335,
239
+ "grad_norm": 0.9431555050834606,
240
+ "learning_rate": 1.7222222222222224e-05,
241
+ "loss": 0.1392,
242
+ "mean_token_accuracy": 0.9550256729125977,
243
+ "num_tokens": 509794.0,
244
+ "step": 26
245
+ },
246
+ {
247
+ "epoch": 0.45,
248
+ "grad_norm": 1.9793286155892176,
249
+ "learning_rate": 1.7111111111111112e-05,
250
+ "loss": 0.2719,
251
+ "mean_token_accuracy": 0.9111931324005127,
252
+ "num_tokens": 527991.0,
253
+ "step": 27
254
+ },
255
+ {
256
+ "epoch": 0.4666666666666667,
257
+ "grad_norm": 1.5957545211368038,
258
+ "learning_rate": 1.7e-05,
259
+ "loss": 0.1977,
260
+ "mean_token_accuracy": 0.9349620342254639,
261
+ "num_tokens": 547103.0,
262
+ "step": 28
263
+ },
264
+ {
265
+ "epoch": 0.48333333333333334,
266
+ "grad_norm": 3.1522248529429553,
267
+ "learning_rate": 1.688888888888889e-05,
268
+ "loss": 0.1857,
269
+ "mean_token_accuracy": 0.9351325631141663,
270
+ "num_tokens": 566491.0,
271
+ "step": 29
272
+ },
273
+ {
274
+ "epoch": 0.5,
275
+ "grad_norm": 1.5505396336667892,
276
+ "learning_rate": 1.677777777777778e-05,
277
+ "loss": 0.2239,
278
+ "mean_token_accuracy": 0.924814760684967,
279
+ "num_tokens": 585075.0,
280
+ "step": 30
281
+ },
282
+ {
283
+ "epoch": 0.5166666666666667,
284
+ "grad_norm": 1.4311688305606354,
285
+ "learning_rate": 1.6666666666666667e-05,
286
+ "loss": 0.2077,
287
+ "mean_token_accuracy": 0.9314337968826294,
288
+ "num_tokens": 605808.0,
289
+ "step": 31
290
+ },
291
+ {
292
+ "epoch": 0.5333333333333333,
293
+ "grad_norm": 1.2265884485285432,
294
+ "learning_rate": 1.6555555555555556e-05,
295
+ "loss": 0.1881,
296
+ "mean_token_accuracy": 0.9358243942260742,
297
+ "num_tokens": 626059.0,
298
+ "step": 32
299
+ },
300
+ {
301
+ "epoch": 0.55,
302
+ "grad_norm": 0.8079478385329993,
303
+ "learning_rate": 1.6444444444444444e-05,
304
+ "loss": 0.1233,
305
+ "mean_token_accuracy": 0.9597011208534241,
306
+ "num_tokens": 650342.0,
307
+ "step": 33
308
+ },
309
+ {
310
+ "epoch": 0.5666666666666667,
311
+ "grad_norm": 1.2783396203778647,
312
+ "learning_rate": 1.6333333333333335e-05,
313
+ "loss": 0.2127,
314
+ "mean_token_accuracy": 0.9305210709571838,
315
+ "num_tokens": 670263.0,
316
+ "step": 34
317
+ },
318
+ {
319
+ "epoch": 0.5833333333333334,
320
+ "grad_norm": 0.9877687041686216,
321
+ "learning_rate": 1.6222222222222223e-05,
322
+ "loss": 0.1746,
323
+ "mean_token_accuracy": 0.9428037405014038,
324
+ "num_tokens": 691344.0,
325
+ "step": 35
326
+ },
327
+ {
328
+ "epoch": 0.6,
329
+ "grad_norm": 1.5309480298196683,
330
+ "learning_rate": 1.6111111111111115e-05,
331
+ "loss": 0.2611,
332
+ "mean_token_accuracy": 0.9084930419921875,
333
+ "num_tokens": 709722.0,
334
+ "step": 36
335
+ },
336
+ {
337
+ "epoch": 0.6166666666666667,
338
+ "grad_norm": 1.3958581151438867,
339
+ "learning_rate": 1.6000000000000003e-05,
340
+ "loss": 0.252,
341
+ "mean_token_accuracy": 0.9160849452018738,
342
+ "num_tokens": 729659.0,
343
+ "step": 37
344
+ },
345
+ {
346
+ "epoch": 0.6333333333333333,
347
+ "grad_norm": 1.4234777494453432,
348
+ "learning_rate": 1.588888888888889e-05,
349
+ "loss": 0.1948,
350
+ "mean_token_accuracy": 0.9306625723838806,
351
+ "num_tokens": 747899.0,
352
+ "step": 38
353
+ },
354
+ {
355
+ "epoch": 0.65,
356
+ "grad_norm": 1.1918567687934656,
357
+ "learning_rate": 1.577777777777778e-05,
358
+ "loss": 0.1923,
359
+ "mean_token_accuracy": 0.9355297088623047,
360
+ "num_tokens": 767996.0,
361
+ "step": 39
362
+ },
363
+ {
364
+ "epoch": 0.6666666666666666,
365
+ "grad_norm": 1.4254154834768535,
366
+ "learning_rate": 1.5666666666666667e-05,
367
+ "loss": 0.2187,
368
+ "mean_token_accuracy": 0.9221748113632202,
369
+ "num_tokens": 786672.0,
370
+ "step": 40
371
+ },
372
+ {
373
+ "epoch": 0.6833333333333333,
374
+ "grad_norm": 1.2363741195385614,
375
+ "learning_rate": 1.555555555555556e-05,
376
+ "loss": 0.1894,
377
+ "mean_token_accuracy": 0.933707058429718,
378
+ "num_tokens": 806857.0,
379
+ "step": 41
380
+ },
381
+ {
382
+ "epoch": 0.7,
383
+ "grad_norm": 1.6616933320839042,
384
+ "learning_rate": 1.5444444444444446e-05,
385
+ "loss": 0.2601,
386
+ "mean_token_accuracy": 0.912670910358429,
387
+ "num_tokens": 825411.0,
388
+ "step": 42
389
+ },
390
+ {
391
+ "epoch": 0.7166666666666667,
392
+ "grad_norm": 1.1594596021236696,
393
+ "learning_rate": 1.5333333333333334e-05,
394
+ "loss": 0.197,
395
+ "mean_token_accuracy": 0.9320076107978821,
396
+ "num_tokens": 845293.0,
397
+ "step": 43
398
+ },
399
+ {
400
+ "epoch": 0.7333333333333333,
401
+ "grad_norm": 1.255447405006153,
402
+ "learning_rate": 1.5222222222222223e-05,
403
+ "loss": 0.2177,
404
+ "mean_token_accuracy": 0.9241234660148621,
405
+ "num_tokens": 864080.0,
406
+ "step": 44
407
+ },
408
+ {
409
+ "epoch": 0.75,
410
+ "grad_norm": 1.3555481042529305,
411
+ "learning_rate": 1.5111111111111112e-05,
412
+ "loss": 0.2464,
413
+ "mean_token_accuracy": 0.9197713136672974,
414
+ "num_tokens": 882551.0,
415
+ "step": 45
416
+ },
417
+ {
418
+ "epoch": 0.7666666666666667,
419
+ "grad_norm": 1.5287024940858407,
420
+ "learning_rate": 1.5000000000000002e-05,
421
+ "loss": 0.2669,
422
+ "mean_token_accuracy": 0.9085003733634949,
423
+ "num_tokens": 901006.0,
424
+ "step": 46
425
+ },
426
+ {
427
+ "epoch": 0.7833333333333333,
428
+ "grad_norm": 1.0365262523875451,
429
+ "learning_rate": 1.488888888888889e-05,
430
+ "loss": 0.1867,
431
+ "mean_token_accuracy": 0.9368327260017395,
432
+ "num_tokens": 920813.0,
433
+ "step": 47
434
+ },
435
+ {
436
+ "epoch": 0.8,
437
+ "grad_norm": 1.1161600400033647,
438
+ "learning_rate": 1.477777777777778e-05,
439
+ "loss": 0.2144,
440
+ "mean_token_accuracy": 0.9287330508232117,
441
+ "num_tokens": 940941.0,
442
+ "step": 48
443
+ },
444
+ {
445
+ "epoch": 0.8166666666666667,
446
+ "grad_norm": 1.2654313555050083,
447
+ "learning_rate": 1.4666666666666666e-05,
448
+ "loss": 0.181,
449
+ "mean_token_accuracy": 0.9393802881240845,
450
+ "num_tokens": 960656.0,
451
+ "step": 49
452
+ },
453
+ {
454
+ "epoch": 0.8333333333333334,
455
+ "grad_norm": 1.1999839375524808,
456
+ "learning_rate": 1.4555555555555556e-05,
457
+ "loss": 0.2165,
458
+ "mean_token_accuracy": 0.924753725528717,
459
+ "num_tokens": 979901.0,
460
+ "step": 50
461
+ },
462
+ {
463
+ "epoch": 0.85,
464
+ "grad_norm": 1.4358719832483007,
465
+ "learning_rate": 1.4444444444444446e-05,
466
+ "loss": 0.2568,
467
+ "mean_token_accuracy": 0.9150856137275696,
468
+ "num_tokens": 997293.0,
469
+ "step": 51
470
+ },
471
+ {
472
+ "epoch": 0.8666666666666667,
473
+ "grad_norm": 0.907854371432327,
474
+ "learning_rate": 1.4333333333333334e-05,
475
+ "loss": 0.1773,
476
+ "mean_token_accuracy": 0.9409731030464172,
477
+ "num_tokens": 1018152.0,
478
+ "step": 52
479
+ },
480
+ {
481
+ "epoch": 0.8833333333333333,
482
+ "grad_norm": 1.3658237813204563,
483
+ "learning_rate": 1.4222222222222224e-05,
484
+ "loss": 0.2182,
485
+ "mean_token_accuracy": 0.9189878702163696,
486
+ "num_tokens": 1035916.0,
487
+ "step": 53
488
+ },
489
+ {
490
+ "epoch": 0.9,
491
+ "grad_norm": 1.0227797653853614,
492
+ "learning_rate": 1.4111111111111113e-05,
493
+ "loss": 0.1937,
494
+ "mean_token_accuracy": 0.9301167130470276,
495
+ "num_tokens": 1055995.0,
496
+ "step": 54
497
+ },
498
+ {
499
+ "epoch": 0.9166666666666666,
500
+ "grad_norm": 1.002167288276357,
501
+ "learning_rate": 1.4e-05,
502
+ "loss": 0.1628,
503
+ "mean_token_accuracy": 0.9427170753479004,
504
+ "num_tokens": 1076188.0,
505
+ "step": 55
506
+ },
507
+ {
508
+ "epoch": 0.9333333333333333,
509
+ "grad_norm": 1.1799372070517915,
510
+ "learning_rate": 1.388888888888889e-05,
511
+ "loss": 0.2145,
512
+ "mean_token_accuracy": 0.925633430480957,
513
+ "num_tokens": 1095323.0,
514
+ "step": 56
515
+ },
516
+ {
517
+ "epoch": 0.95,
518
+ "grad_norm": 1.9565071620010974,
519
+ "learning_rate": 1.377777777777778e-05,
520
+ "loss": 0.2276,
521
+ "mean_token_accuracy": 0.923713207244873,
522
+ "num_tokens": 1113823.0,
523
+ "step": 57
524
+ },
525
+ {
526
+ "epoch": 0.9666666666666667,
527
+ "grad_norm": 1.3720630422421265,
528
+ "learning_rate": 1.3666666666666667e-05,
529
+ "loss": 0.2254,
530
+ "mean_token_accuracy": 0.9204455018043518,
531
+ "num_tokens": 1131913.0,
532
+ "step": 58
533
+ },
534
+ {
535
+ "epoch": 0.9833333333333333,
536
+ "grad_norm": 1.2312026050291756,
537
+ "learning_rate": 1.3555555555555557e-05,
538
+ "loss": 0.2288,
539
+ "mean_token_accuracy": 0.9231975078582764,
540
+ "num_tokens": 1150068.0,
541
+ "step": 59
542
+ },
543
+ {
544
+ "epoch": 1.0,
545
+ "grad_norm": 1.0535788172725804,
546
+ "learning_rate": 1.3444444444444447e-05,
547
+ "loss": 0.1853,
548
+ "mean_token_accuracy": 0.9440000057220459,
549
+ "num_tokens": 1165110.0,
550
+ "step": 60
551
+ },
552
+ {
553
+ "epoch": 1.0166666666666666,
554
+ "grad_norm": 1.1158002070455915,
555
+ "learning_rate": 1.3333333333333333e-05,
556
+ "loss": 0.1817,
557
+ "mean_token_accuracy": 0.937036395072937,
558
+ "num_tokens": 1183696.0,
559
+ "step": 61
560
+ },
561
+ {
562
+ "epoch": 1.0333333333333334,
563
+ "grad_norm": 1.0736249727571867,
564
+ "learning_rate": 1.3222222222222223e-05,
565
+ "loss": 0.1726,
566
+ "mean_token_accuracy": 0.936906635761261,
567
+ "num_tokens": 1201818.0,
568
+ "step": 62
569
+ },
570
+ {
571
+ "epoch": 1.05,
572
+ "grad_norm": 0.9326362452347312,
573
+ "learning_rate": 1.3111111111111113e-05,
574
+ "loss": 0.1497,
575
+ "mean_token_accuracy": 0.9461251497268677,
576
+ "num_tokens": 1222105.0,
577
+ "step": 63
578
+ },
579
+ {
580
+ "epoch": 1.0666666666666667,
581
+ "grad_norm": 1.0392083191471302,
582
+ "learning_rate": 1.3000000000000001e-05,
583
+ "loss": 0.1642,
584
+ "mean_token_accuracy": 0.9368287920951843,
585
+ "num_tokens": 1241483.0,
586
+ "step": 64
587
+ },
588
+ {
589
+ "epoch": 1.0833333333333333,
590
+ "grad_norm": 1.147040989505759,
591
+ "learning_rate": 1.288888888888889e-05,
592
+ "loss": 0.1752,
593
+ "mean_token_accuracy": 0.9369705319404602,
594
+ "num_tokens": 1260457.0,
595
+ "step": 65
596
+ },
597
+ {
598
+ "epoch": 1.1,
599
+ "grad_norm": 0.9805982619164562,
600
+ "learning_rate": 1.2777777777777777e-05,
601
+ "loss": 0.1541,
602
+ "mean_token_accuracy": 0.9449800252914429,
603
+ "num_tokens": 1279517.0,
604
+ "step": 66
605
+ },
606
+ {
607
+ "epoch": 1.1166666666666667,
608
+ "grad_norm": 0.9058555751871202,
609
+ "learning_rate": 1.2666666666666667e-05,
610
+ "loss": 0.136,
611
+ "mean_token_accuracy": 0.9510924816131592,
612
+ "num_tokens": 1299484.0,
613
+ "step": 67
614
+ },
615
+ {
616
+ "epoch": 1.1333333333333333,
617
+ "grad_norm": 0.8685189058450895,
618
+ "learning_rate": 1.2555555555555557e-05,
619
+ "loss": 0.125,
620
+ "mean_token_accuracy": 0.9575818777084351,
621
+ "num_tokens": 1319473.0,
622
+ "step": 68
623
+ },
624
+ {
625
+ "epoch": 1.15,
626
+ "grad_norm": 0.7442438614909151,
627
+ "learning_rate": 1.2444444444444446e-05,
628
+ "loss": 0.1179,
629
+ "mean_token_accuracy": 0.957948625087738,
630
+ "num_tokens": 1341520.0,
631
+ "step": 69
632
+ },
633
+ {
634
+ "epoch": 1.1666666666666667,
635
+ "grad_norm": 1.2278003815150234,
636
+ "learning_rate": 1.2333333333333334e-05,
637
+ "loss": 0.186,
638
+ "mean_token_accuracy": 0.9343335628509521,
639
+ "num_tokens": 1359186.0,
640
+ "step": 70
641
+ },
642
+ {
643
+ "epoch": 1.1833333333333333,
644
+ "grad_norm": 1.0420462136657762,
645
+ "learning_rate": 1.2222222222222224e-05,
646
+ "loss": 0.153,
647
+ "mean_token_accuracy": 0.9469709396362305,
648
+ "num_tokens": 1378315.0,
649
+ "step": 71
650
+ },
651
+ {
652
+ "epoch": 1.2,
653
+ "grad_norm": 1.0380048193076985,
654
+ "learning_rate": 1.211111111111111e-05,
655
+ "loss": 0.1436,
656
+ "mean_token_accuracy": 0.9483470916748047,
657
+ "num_tokens": 1398153.0,
658
+ "step": 72
659
+ },
660
+ {
661
+ "epoch": 1.2166666666666668,
662
+ "grad_norm": 1.0084621189290743,
663
+ "learning_rate": 1.2e-05,
664
+ "loss": 0.1615,
665
+ "mean_token_accuracy": 0.9417263865470886,
666
+ "num_tokens": 1417629.0,
667
+ "step": 73
668
+ },
669
+ {
670
+ "epoch": 1.2333333333333334,
671
+ "grad_norm": 0.9505316501027468,
672
+ "learning_rate": 1.188888888888889e-05,
673
+ "loss": 0.1445,
674
+ "mean_token_accuracy": 0.9472274780273438,
675
+ "num_tokens": 1437025.0,
676
+ "step": 74
677
+ },
678
+ {
679
+ "epoch": 1.25,
680
+ "grad_norm": 1.1884286204876424,
681
+ "learning_rate": 1.177777777777778e-05,
682
+ "loss": 0.1698,
683
+ "mean_token_accuracy": 0.9374273419380188,
684
+ "num_tokens": 1455251.0,
685
+ "step": 75
686
+ },
687
+ {
688
+ "epoch": 1.2666666666666666,
689
+ "grad_norm": 1.2379531503777974,
690
+ "learning_rate": 1.1666666666666668e-05,
691
+ "loss": 0.1899,
692
+ "mean_token_accuracy": 0.9276366233825684,
693
+ "num_tokens": 1473505.0,
694
+ "step": 76
695
+ },
696
+ {
697
+ "epoch": 1.2833333333333332,
698
+ "grad_norm": 0.9831497253026844,
699
+ "learning_rate": 1.1555555555555556e-05,
700
+ "loss": 0.159,
701
+ "mean_token_accuracy": 0.9436038732528687,
702
+ "num_tokens": 1493095.0,
703
+ "step": 77
704
+ },
705
+ {
706
+ "epoch": 1.3,
707
+ "grad_norm": 0.9439881364034777,
708
+ "learning_rate": 1.1444444444444444e-05,
709
+ "loss": 0.1398,
710
+ "mean_token_accuracy": 0.951481282711029,
711
+ "num_tokens": 1512761.0,
712
+ "step": 78
713
+ },
714
+ {
715
+ "epoch": 1.3166666666666667,
716
+ "grad_norm": 1.1347468457271879,
717
+ "learning_rate": 1.1333333333333334e-05,
718
+ "loss": 0.1735,
719
+ "mean_token_accuracy": 0.9395575523376465,
720
+ "num_tokens": 1531560.0,
721
+ "step": 79
722
+ },
723
+ {
724
+ "epoch": 1.3333333333333333,
725
+ "grad_norm": 1.3653117110046264,
726
+ "learning_rate": 1.1222222222222224e-05,
727
+ "loss": 0.2011,
728
+ "mean_token_accuracy": 0.9258978962898254,
729
+ "num_tokens": 1549916.0,
730
+ "step": 80
731
+ },
732
+ {
733
+ "epoch": 1.35,
734
+ "grad_norm": 0.9813633271839456,
735
+ "learning_rate": 1.1111111111111113e-05,
736
+ "loss": 0.1372,
737
+ "mean_token_accuracy": 0.9503588676452637,
738
+ "num_tokens": 1571334.0,
739
+ "step": 81
740
+ },
741
+ {
742
+ "epoch": 1.3666666666666667,
743
+ "grad_norm": 0.7962753001770728,
744
+ "learning_rate": 1.1000000000000001e-05,
745
+ "loss": 0.1172,
746
+ "mean_token_accuracy": 0.9567482471466064,
747
+ "num_tokens": 1592652.0,
748
+ "step": 82
749
+ },
750
+ {
751
+ "epoch": 1.3833333333333333,
752
+ "grad_norm": 0.913780453529574,
753
+ "learning_rate": 1.088888888888889e-05,
754
+ "loss": 0.1236,
755
+ "mean_token_accuracy": 0.9562375545501709,
756
+ "num_tokens": 1612736.0,
757
+ "step": 83
758
+ },
759
+ {
760
+ "epoch": 1.4,
761
+ "grad_norm": 1.0378983131114818,
762
+ "learning_rate": 1.0777777777777778e-05,
763
+ "loss": 0.1517,
764
+ "mean_token_accuracy": 0.9468337297439575,
765
+ "num_tokens": 1631698.0,
766
+ "step": 84
767
+ },
768
+ {
769
+ "epoch": 1.4166666666666667,
770
+ "grad_norm": 0.8763910012325973,
771
+ "learning_rate": 1.0666666666666667e-05,
772
+ "loss": 0.1366,
773
+ "mean_token_accuracy": 0.9536712169647217,
774
+ "num_tokens": 1651859.0,
775
+ "step": 85
776
+ },
777
+ {
778
+ "epoch": 1.4333333333333333,
779
+ "grad_norm": 0.7078652833933885,
780
+ "learning_rate": 1.0555555555555557e-05,
781
+ "loss": 0.1024,
782
+ "mean_token_accuracy": 0.9619000554084778,
783
+ "num_tokens": 1673006.0,
784
+ "step": 86
785
+ },
786
+ {
787
+ "epoch": 1.45,
788
+ "grad_norm": 0.8659401761097084,
789
+ "learning_rate": 1.0444444444444445e-05,
790
+ "loss": 0.1254,
791
+ "mean_token_accuracy": 0.9535650014877319,
792
+ "num_tokens": 1692728.0,
793
+ "step": 87
794
+ },
795
+ {
796
+ "epoch": 1.4666666666666668,
797
+ "grad_norm": 0.8708809194871703,
798
+ "learning_rate": 1.0333333333333335e-05,
799
+ "loss": 0.1439,
800
+ "mean_token_accuracy": 0.9477262496948242,
801
+ "num_tokens": 1712396.0,
802
+ "step": 88
803
+ },
804
+ {
805
+ "epoch": 1.4833333333333334,
806
+ "grad_norm": 1.012787064893325,
807
+ "learning_rate": 1.0222222222222223e-05,
808
+ "loss": 0.1418,
809
+ "mean_token_accuracy": 0.9502722024917603,
810
+ "num_tokens": 1732251.0,
811
+ "step": 89
812
+ },
813
+ {
814
+ "epoch": 1.5,
815
+ "grad_norm": 1.20605467124662,
816
+ "learning_rate": 1.0111111111111111e-05,
817
+ "loss": 0.1648,
818
+ "mean_token_accuracy": 0.9385513067245483,
819
+ "num_tokens": 1751139.0,
820
+ "step": 90
821
+ },
822
+ {
823
+ "epoch": 1.5166666666666666,
824
+ "grad_norm": 0.7709893587047212,
825
+ "learning_rate": 1e-05,
826
+ "loss": 0.1143,
827
+ "mean_token_accuracy": 0.9584763050079346,
828
+ "num_tokens": 1772929.0,
829
+ "step": 91
830
+ },
831
+ {
832
+ "epoch": 1.5333333333333332,
833
+ "grad_norm": 0.9143355507406298,
834
+ "learning_rate": 9.88888888888889e-06,
835
+ "loss": 0.1332,
836
+ "mean_token_accuracy": 0.9550284743309021,
837
+ "num_tokens": 1792455.0,
838
+ "step": 92
839
+ },
840
+ {
841
+ "epoch": 1.55,
842
+ "grad_norm": 1.156665256897338,
843
+ "learning_rate": 9.777777777777779e-06,
844
+ "loss": 0.1452,
845
+ "mean_token_accuracy": 0.9457477927207947,
846
+ "num_tokens": 1810962.0,
847
+ "step": 93
848
+ },
849
+ {
850
+ "epoch": 1.5666666666666667,
851
+ "grad_norm": 1.0204063013809,
852
+ "learning_rate": 9.666666666666667e-06,
853
+ "loss": 0.1504,
854
+ "mean_token_accuracy": 0.944669783115387,
855
+ "num_tokens": 1830171.0,
856
+ "step": 94
857
+ },
858
+ {
859
+ "epoch": 1.5833333333333335,
860
+ "grad_norm": 1.13940818302726,
861
+ "learning_rate": 9.555555555555556e-06,
862
+ "loss": 0.1624,
863
+ "mean_token_accuracy": 0.9425520896911621,
864
+ "num_tokens": 1849120.0,
865
+ "step": 95
866
+ },
867
+ {
868
+ "epoch": 1.6,
869
+ "grad_norm": 1.1239662031696884,
870
+ "learning_rate": 9.444444444444445e-06,
871
+ "loss": 0.169,
872
+ "mean_token_accuracy": 0.941411018371582,
873
+ "num_tokens": 1868698.0,
874
+ "step": 96
875
+ },
876
+ {
877
+ "epoch": 1.6166666666666667,
878
+ "grad_norm": 0.9337438130011902,
879
+ "learning_rate": 9.333333333333334e-06,
880
+ "loss": 0.1127,
881
+ "mean_token_accuracy": 0.9583436846733093,
882
+ "num_tokens": 1889793.0,
883
+ "step": 97
884
+ },
885
+ {
886
+ "epoch": 1.6333333333333333,
887
+ "grad_norm": 1.2548785873636994,
888
+ "learning_rate": 9.222222222222224e-06,
889
+ "loss": 0.1874,
890
+ "mean_token_accuracy": 0.9316017031669617,
891
+ "num_tokens": 1907473.0,
892
+ "step": 98
893
+ },
894
+ {
895
+ "epoch": 1.65,
896
+ "grad_norm": 1.1746557760923275,
897
+ "learning_rate": 9.111111111111112e-06,
898
+ "loss": 0.1915,
899
+ "mean_token_accuracy": 0.9325609803199768,
900
+ "num_tokens": 1926318.0,
901
+ "step": 99
902
+ },
903
+ {
904
+ "epoch": 1.6666666666666665,
905
+ "grad_norm": 0.9306519879019831,
906
+ "learning_rate": 9e-06,
907
+ "loss": 0.1331,
908
+ "mean_token_accuracy": 0.9495912790298462,
909
+ "num_tokens": 1946708.0,
910
+ "step": 100
911
+ },
912
+ {
913
+ "epoch": 1.6833333333333333,
914
+ "grad_norm": 0.9446275954390885,
915
+ "learning_rate": 8.888888888888888e-06,
916
+ "loss": 0.1434,
917
+ "mean_token_accuracy": 0.9497577548027039,
918
+ "num_tokens": 1965342.0,
919
+ "step": 101
920
+ },
921
+ {
922
+ "epoch": 1.7,
923
+ "grad_norm": 0.9234966150999687,
924
+ "learning_rate": 8.777777777777778e-06,
925
+ "loss": 0.1376,
926
+ "mean_token_accuracy": 0.9505731463432312,
927
+ "num_tokens": 1985111.0,
928
+ "step": 102
929
+ },
930
+ {
931
+ "epoch": 1.7166666666666668,
932
+ "grad_norm": 0.9537386059477831,
933
+ "learning_rate": 8.666666666666668e-06,
934
+ "loss": 0.1376,
935
+ "mean_token_accuracy": 0.9508804678916931,
936
+ "num_tokens": 2004615.0,
937
+ "step": 103
938
+ },
939
+ {
940
+ "epoch": 1.7333333333333334,
941
+ "grad_norm": 0.9913708002681217,
942
+ "learning_rate": 8.555555555555556e-06,
943
+ "loss": 0.1628,
944
+ "mean_token_accuracy": 0.9396049380302429,
945
+ "num_tokens": 2023853.0,
946
+ "step": 104
947
+ },
948
+ {
949
+ "epoch": 1.75,
950
+ "grad_norm": 1.1848216877825122,
951
+ "learning_rate": 8.444444444444446e-06,
952
+ "loss": 0.1723,
953
+ "mean_token_accuracy": 0.9336273670196533,
954
+ "num_tokens": 2041684.0,
955
+ "step": 105
956
+ },
957
+ {
958
+ "epoch": 1.7666666666666666,
959
+ "grad_norm": 0.9897585477322013,
960
+ "learning_rate": 8.333333333333334e-06,
961
+ "loss": 0.14,
962
+ "mean_token_accuracy": 0.9489489197731018,
963
+ "num_tokens": 2060735.0,
964
+ "step": 106
965
+ },
966
+ {
967
+ "epoch": 1.7833333333333332,
968
+ "grad_norm": 0.6769645173431437,
969
+ "learning_rate": 8.222222222222222e-06,
970
+ "loss": 0.1125,
971
+ "mean_token_accuracy": 0.9590517282485962,
972
+ "num_tokens": 2081676.0,
973
+ "step": 107
974
+ },
975
+ {
976
+ "epoch": 1.8,
977
+ "grad_norm": 0.9941938323842807,
978
+ "learning_rate": 8.111111111111112e-06,
979
+ "loss": 0.1558,
980
+ "mean_token_accuracy": 0.9427565932273865,
981
+ "num_tokens": 2100126.0,
982
+ "step": 108
983
+ },
984
+ {
985
+ "epoch": 1.8166666666666667,
986
+ "grad_norm": 1.023487530043029,
987
+ "learning_rate": 8.000000000000001e-06,
988
+ "loss": 0.1498,
989
+ "mean_token_accuracy": 0.9459511041641235,
990
+ "num_tokens": 2118412.0,
991
+ "step": 109
992
+ },
993
+ {
994
+ "epoch": 1.8333333333333335,
995
+ "grad_norm": 1.0442509083619982,
996
+ "learning_rate": 7.88888888888889e-06,
997
+ "loss": 0.1528,
998
+ "mean_token_accuracy": 0.9426274299621582,
999
+ "num_tokens": 2136945.0,
1000
+ "step": 110
1001
+ },
1002
+ {
1003
+ "epoch": 1.85,
1004
+ "grad_norm": 0.7382938848577654,
1005
+ "learning_rate": 7.77777777777778e-06,
1006
+ "loss": 0.1069,
1007
+ "mean_token_accuracy": 0.9606086611747742,
1008
+ "num_tokens": 2158142.0,
1009
+ "step": 111
1010
+ },
1011
+ {
1012
+ "epoch": 1.8666666666666667,
1013
+ "grad_norm": 1.013004919544077,
1014
+ "learning_rate": 7.666666666666667e-06,
1015
+ "loss": 0.1301,
1016
+ "mean_token_accuracy": 0.9497557282447815,
1017
+ "num_tokens": 2176933.0,
1018
+ "step": 112
1019
+ },
1020
+ {
1021
+ "epoch": 1.8833333333333333,
1022
+ "grad_norm": 1.0119787562037492,
1023
+ "learning_rate": 7.555555555555556e-06,
1024
+ "loss": 0.1566,
1025
+ "mean_token_accuracy": 0.9420549869537354,
1026
+ "num_tokens": 2196697.0,
1027
+ "step": 113
1028
+ },
1029
+ {
1030
+ "epoch": 1.9,
1031
+ "grad_norm": 0.9854931097065066,
1032
+ "learning_rate": 7.444444444444445e-06,
1033
+ "loss": 0.1534,
1034
+ "mean_token_accuracy": 0.9418057799339294,
1035
+ "num_tokens": 2215923.0,
1036
+ "step": 114
1037
+ },
1038
+ {
1039
+ "epoch": 1.9166666666666665,
1040
+ "grad_norm": 0.7144804965252481,
1041
+ "learning_rate": 7.333333333333333e-06,
1042
+ "loss": 0.1037,
1043
+ "mean_token_accuracy": 0.9651133418083191,
1044
+ "num_tokens": 2236922.0,
1045
+ "step": 115
1046
+ },
1047
+ {
1048
+ "epoch": 1.9333333333333333,
1049
+ "grad_norm": 0.7694761724271274,
1050
+ "learning_rate": 7.222222222222223e-06,
1051
+ "loss": 0.1138,
1052
+ "mean_token_accuracy": 0.9599701762199402,
1053
+ "num_tokens": 2258029.0,
1054
+ "step": 116
1055
+ },
1056
+ {
1057
+ "epoch": 1.95,
1058
+ "grad_norm": 0.9606224762156166,
1059
+ "learning_rate": 7.111111111111112e-06,
1060
+ "loss": 0.1588,
1061
+ "mean_token_accuracy": 0.9443244338035583,
1062
+ "num_tokens": 2277091.0,
1063
+ "step": 117
1064
+ },
1065
+ {
1066
+ "epoch": 1.9666666666666668,
1067
+ "grad_norm": 1.0937626624760368,
1068
+ "learning_rate": 7e-06,
1069
+ "loss": 0.1532,
1070
+ "mean_token_accuracy": 0.9443029761314392,
1071
+ "num_tokens": 2296417.0,
1072
+ "step": 118
1073
+ },
1074
+ {
1075
+ "epoch": 1.9833333333333334,
1076
+ "grad_norm": 1.0711892173260553,
1077
+ "learning_rate": 6.88888888888889e-06,
1078
+ "loss": 0.1595,
1079
+ "mean_token_accuracy": 0.9443521499633789,
1080
+ "num_tokens": 2315489.0,
1081
+ "step": 119
1082
+ },
1083
+ {
1084
+ "epoch": 2.0,
1085
+ "grad_norm": 0.8768653402030852,
1086
+ "learning_rate": 6.777777777777779e-06,
1087
+ "loss": 0.1165,
1088
+ "mean_token_accuracy": 0.9577861428260803,
1089
+ "num_tokens": 2329544.0,
1090
+ "step": 120
1091
+ },
1092
+ {
1093
+ "epoch": 2.0166666666666666,
1094
+ "grad_norm": 0.6251281839168465,
1095
+ "learning_rate": 6.666666666666667e-06,
1096
+ "loss": 0.0771,
1097
+ "mean_token_accuracy": 0.9738717079162598,
1098
+ "num_tokens": 2351006.0,
1099
+ "step": 121
1100
+ },
1101
+ {
1102
+ "epoch": 2.033333333333333,
1103
+ "grad_norm": 0.6284390720490242,
1104
+ "learning_rate": 6.555555555555556e-06,
1105
+ "loss": 0.0833,
1106
+ "mean_token_accuracy": 0.9683251976966858,
1107
+ "num_tokens": 2371636.0,
1108
+ "step": 122
1109
+ },
1110
+ {
1111
+ "epoch": 2.05,
1112
+ "grad_norm": 0.6826995248721669,
1113
+ "learning_rate": 6.444444444444445e-06,
1114
+ "loss": 0.093,
1115
+ "mean_token_accuracy": 0.9684882760047913,
1116
+ "num_tokens": 2391742.0,
1117
+ "step": 123
1118
+ },
1119
+ {
1120
+ "epoch": 2.066666666666667,
1121
+ "grad_norm": 0.6985483544899995,
1122
+ "learning_rate": 6.333333333333333e-06,
1123
+ "loss": 0.0874,
1124
+ "mean_token_accuracy": 0.9688146710395813,
1125
+ "num_tokens": 2411562.0,
1126
+ "step": 124
1127
+ },
1128
+ {
1129
+ "epoch": 2.0833333333333335,
1130
+ "grad_norm": 0.7179963812086702,
1131
+ "learning_rate": 6.222222222222223e-06,
1132
+ "loss": 0.0947,
1133
+ "mean_token_accuracy": 0.9637842774391174,
1134
+ "num_tokens": 2430887.0,
1135
+ "step": 125
1136
+ },
1137
+ {
1138
+ "epoch": 2.1,
1139
+ "grad_norm": 0.7340775462108364,
1140
+ "learning_rate": 6.111111111111112e-06,
1141
+ "loss": 0.0882,
1142
+ "mean_token_accuracy": 0.968779444694519,
1143
+ "num_tokens": 2450324.0,
1144
+ "step": 126
1145
+ },
1146
+ {
1147
+ "epoch": 2.1166666666666667,
1148
+ "grad_norm": 0.6971941014215697,
1149
+ "learning_rate": 6e-06,
1150
+ "loss": 0.0865,
1151
+ "mean_token_accuracy": 0.966270387172699,
1152
+ "num_tokens": 2470605.0,
1153
+ "step": 127
1154
+ },
1155
+ {
1156
+ "epoch": 2.1333333333333333,
1157
+ "grad_norm": 0.7708208981885679,
1158
+ "learning_rate": 5.88888888888889e-06,
1159
+ "loss": 0.0936,
1160
+ "mean_token_accuracy": 0.9645907282829285,
1161
+ "num_tokens": 2489281.0,
1162
+ "step": 128
1163
+ },
1164
+ {
1165
+ "epoch": 2.15,
1166
+ "grad_norm": 1.063746925464334,
1167
+ "learning_rate": 5.777777777777778e-06,
1168
+ "loss": 0.1047,
1169
+ "mean_token_accuracy": 0.9620683789253235,
1170
+ "num_tokens": 2508213.0,
1171
+ "step": 129
1172
+ },
1173
+ {
1174
+ "epoch": 2.1666666666666665,
1175
+ "grad_norm": 0.85374641121885,
1176
+ "learning_rate": 5.666666666666667e-06,
1177
+ "loss": 0.0934,
1178
+ "mean_token_accuracy": 0.9634836316108704,
1179
+ "num_tokens": 2526747.0,
1180
+ "step": 130
1181
+ },
1182
+ {
1183
+ "epoch": 2.183333333333333,
1184
+ "grad_norm": 0.8620800950130304,
1185
+ "learning_rate": 5.555555555555557e-06,
1186
+ "loss": 0.1008,
1187
+ "mean_token_accuracy": 0.9645389914512634,
1188
+ "num_tokens": 2545705.0,
1189
+ "step": 131
1190
+ },
1191
+ {
1192
+ "epoch": 2.2,
1193
+ "grad_norm": 0.7793400238647186,
1194
+ "learning_rate": 5.444444444444445e-06,
1195
+ "loss": 0.0896,
1196
+ "mean_token_accuracy": 0.966309130191803,
1197
+ "num_tokens": 2566036.0,
1198
+ "step": 132
1199
+ },
1200
+ {
1201
+ "epoch": 2.216666666666667,
1202
+ "grad_norm": 0.8854628019833792,
1203
+ "learning_rate": 5.333333333333334e-06,
1204
+ "loss": 0.0883,
1205
+ "mean_token_accuracy": 0.9674826264381409,
1206
+ "num_tokens": 2584575.0,
1207
+ "step": 133
1208
+ },
1209
+ {
1210
+ "epoch": 2.2333333333333334,
1211
+ "grad_norm": 0.9099694952637853,
1212
+ "learning_rate": 5.2222222222222226e-06,
1213
+ "loss": 0.1028,
1214
+ "mean_token_accuracy": 0.9623646140098572,
1215
+ "num_tokens": 2603271.0,
1216
+ "step": 134
1217
+ },
1218
+ {
1219
+ "epoch": 2.25,
1220
+ "grad_norm": 1.2415591598728333,
1221
+ "learning_rate": 5.1111111111111115e-06,
1222
+ "loss": 0.13,
1223
+ "mean_token_accuracy": 0.951812744140625,
1224
+ "num_tokens": 2620691.0,
1225
+ "step": 135
1226
+ },
1227
+ {
1228
+ "epoch": 2.2666666666666666,
1229
+ "grad_norm": 0.8805897450359303,
1230
+ "learning_rate": 5e-06,
1231
+ "loss": 0.0901,
1232
+ "mean_token_accuracy": 0.9666962623596191,
1233
+ "num_tokens": 2640489.0,
1234
+ "step": 136
1235
+ },
1236
+ {
1237
+ "epoch": 2.283333333333333,
1238
+ "grad_norm": 0.6831112090735907,
1239
+ "learning_rate": 4.888888888888889e-06,
1240
+ "loss": 0.0719,
1241
+ "mean_token_accuracy": 0.9733719825744629,
1242
+ "num_tokens": 2661139.0,
1243
+ "step": 137
1244
+ },
1245
+ {
1246
+ "epoch": 2.3,
1247
+ "grad_norm": 0.9359785185685812,
1248
+ "learning_rate": 4.777777777777778e-06,
1249
+ "loss": 0.0979,
1250
+ "mean_token_accuracy": 0.9644399881362915,
1251
+ "num_tokens": 2681134.0,
1252
+ "step": 138
1253
+ },
1254
+ {
1255
+ "epoch": 2.3166666666666664,
1256
+ "grad_norm": 0.6982783617868149,
1257
+ "learning_rate": 4.666666666666667e-06,
1258
+ "loss": 0.0802,
1259
+ "mean_token_accuracy": 0.9708402156829834,
1260
+ "num_tokens": 2701418.0,
1261
+ "step": 139
1262
+ },
1263
+ {
1264
+ "epoch": 2.3333333333333335,
1265
+ "grad_norm": 0.8356985024729287,
1266
+ "learning_rate": 4.555555555555556e-06,
1267
+ "loss": 0.1037,
1268
+ "mean_token_accuracy": 0.9611542820930481,
1269
+ "num_tokens": 2720773.0,
1270
+ "step": 140
1271
+ },
1272
+ {
1273
+ "epoch": 2.35,
1274
+ "grad_norm": 0.9862372490871846,
1275
+ "learning_rate": 4.444444444444444e-06,
1276
+ "loss": 0.1067,
1277
+ "mean_token_accuracy": 0.9594425559043884,
1278
+ "num_tokens": 2739428.0,
1279
+ "step": 141
1280
+ },
1281
+ {
1282
+ "epoch": 2.3666666666666667,
1283
+ "grad_norm": 0.623294732436491,
1284
+ "learning_rate": 4.333333333333334e-06,
1285
+ "loss": 0.0695,
1286
+ "mean_token_accuracy": 0.9733567833900452,
1287
+ "num_tokens": 2760440.0,
1288
+ "step": 142
1289
+ },
1290
+ {
1291
+ "epoch": 2.3833333333333333,
1292
+ "grad_norm": 0.7322830332993291,
1293
+ "learning_rate": 4.222222222222223e-06,
1294
+ "loss": 0.0889,
1295
+ "mean_token_accuracy": 0.9665079116821289,
1296
+ "num_tokens": 2780009.0,
1297
+ "step": 143
1298
+ },
1299
+ {
1300
+ "epoch": 2.4,
1301
+ "grad_norm": 0.8143415765985169,
1302
+ "learning_rate": 4.111111111111111e-06,
1303
+ "loss": 0.0951,
1304
+ "mean_token_accuracy": 0.9636101126670837,
1305
+ "num_tokens": 2799989.0,
1306
+ "step": 144
1307
+ },
1308
+ {
1309
+ "epoch": 2.4166666666666665,
1310
+ "grad_norm": 0.546869291947266,
1311
+ "learning_rate": 4.000000000000001e-06,
1312
+ "loss": 0.0651,
1313
+ "mean_token_accuracy": 0.9757785201072693,
1314
+ "num_tokens": 2821423.0,
1315
+ "step": 145
1316
+ },
1317
+ {
1318
+ "epoch": 2.4333333333333336,
1319
+ "grad_norm": 0.8270848313125879,
1320
+ "learning_rate": 3.88888888888889e-06,
1321
+ "loss": 0.0915,
1322
+ "mean_token_accuracy": 0.9669610857963562,
1323
+ "num_tokens": 2840604.0,
1324
+ "step": 146
1325
+ },
1326
+ {
1327
+ "epoch": 2.45,
1328
+ "grad_norm": 0.8517198133246286,
1329
+ "learning_rate": 3.777777777777778e-06,
1330
+ "loss": 0.0932,
1331
+ "mean_token_accuracy": 0.964799702167511,
1332
+ "num_tokens": 2859437.0,
1333
+ "step": 147
1334
+ },
1335
+ {
1336
+ "epoch": 2.466666666666667,
1337
+ "grad_norm": 0.9674954444130963,
1338
+ "learning_rate": 3.6666666666666666e-06,
1339
+ "loss": 0.0995,
1340
+ "mean_token_accuracy": 0.9642043709754944,
1341
+ "num_tokens": 2878635.0,
1342
+ "step": 148
1343
+ },
1344
+ {
1345
+ "epoch": 2.4833333333333334,
1346
+ "grad_norm": 0.8923432338281196,
1347
+ "learning_rate": 3.555555555555556e-06,
1348
+ "loss": 0.107,
1349
+ "mean_token_accuracy": 0.9613018035888672,
1350
+ "num_tokens": 2897866.0,
1351
+ "step": 149
1352
+ },
1353
+ {
1354
+ "epoch": 2.5,
1355
+ "grad_norm": 0.5948440836171763,
1356
+ "learning_rate": 3.444444444444445e-06,
1357
+ "loss": 0.0722,
1358
+ "mean_token_accuracy": 0.9716657996177673,
1359
+ "num_tokens": 2920541.0,
1360
+ "step": 150
1361
+ },
1362
+ {
1363
+ "epoch": 2.5166666666666666,
1364
+ "grad_norm": 0.6997082703093433,
1365
+ "learning_rate": 3.3333333333333333e-06,
1366
+ "loss": 0.0818,
1367
+ "mean_token_accuracy": 0.9700831770896912,
1368
+ "num_tokens": 2941043.0,
1369
+ "step": 151
1370
+ },
1371
+ {
1372
+ "epoch": 2.533333333333333,
1373
+ "grad_norm": 0.6853424324861723,
1374
+ "learning_rate": 3.2222222222222227e-06,
1375
+ "loss": 0.0699,
1376
+ "mean_token_accuracy": 0.9737975597381592,
1377
+ "num_tokens": 2962451.0,
1378
+ "step": 152
1379
+ },
1380
+ {
1381
+ "epoch": 2.55,
1382
+ "grad_norm": 0.788856800633058,
1383
+ "learning_rate": 3.1111111111111116e-06,
1384
+ "loss": 0.0951,
1385
+ "mean_token_accuracy": 0.9657984972000122,
1386
+ "num_tokens": 2983102.0,
1387
+ "step": 153
1388
+ },
1389
+ {
1390
+ "epoch": 2.5666666666666664,
1391
+ "grad_norm": 0.8049580781436556,
1392
+ "learning_rate": 3e-06,
1393
+ "loss": 0.0874,
1394
+ "mean_token_accuracy": 0.9658728837966919,
1395
+ "num_tokens": 3002754.0,
1396
+ "step": 154
1397
+ },
1398
+ {
1399
+ "epoch": 2.5833333333333335,
1400
+ "grad_norm": 0.6468847476444607,
1401
+ "learning_rate": 2.888888888888889e-06,
1402
+ "loss": 0.0718,
1403
+ "mean_token_accuracy": 0.9740763902664185,
1404
+ "num_tokens": 3023792.0,
1405
+ "step": 155
1406
+ },
1407
+ {
1408
+ "epoch": 2.6,
1409
+ "grad_norm": 0.7790527794056367,
1410
+ "learning_rate": 2.7777777777777783e-06,
1411
+ "loss": 0.0907,
1412
+ "mean_token_accuracy": 0.9634305834770203,
1413
+ "num_tokens": 3043717.0,
1414
+ "step": 156
1415
+ },
1416
+ {
1417
+ "epoch": 2.6166666666666667,
1418
+ "grad_norm": 0.7784804869782793,
1419
+ "learning_rate": 2.666666666666667e-06,
1420
+ "loss": 0.0813,
1421
+ "mean_token_accuracy": 0.9687763452529907,
1422
+ "num_tokens": 3062697.0,
1423
+ "step": 157
1424
+ },
1425
+ {
1426
+ "epoch": 2.6333333333333333,
1427
+ "grad_norm": 0.8695866199163134,
1428
+ "learning_rate": 2.5555555555555557e-06,
1429
+ "loss": 0.1028,
1430
+ "mean_token_accuracy": 0.9597998857498169,
1431
+ "num_tokens": 3081540.0,
1432
+ "step": 158
1433
+ },
1434
+ {
1435
+ "epoch": 2.65,
1436
+ "grad_norm": 0.8264331195451216,
1437
+ "learning_rate": 2.4444444444444447e-06,
1438
+ "loss": 0.0884,
1439
+ "mean_token_accuracy": 0.965327262878418,
1440
+ "num_tokens": 3100748.0,
1441
+ "step": 159
1442
+ },
1443
+ {
1444
+ "epoch": 2.6666666666666665,
1445
+ "grad_norm": 0.8336042061118125,
1446
+ "learning_rate": 2.3333333333333336e-06,
1447
+ "loss": 0.0938,
1448
+ "mean_token_accuracy": 0.9615654349327087,
1449
+ "num_tokens": 3119513.0,
1450
+ "step": 160
1451
+ },
1452
+ {
1453
+ "epoch": 2.6833333333333336,
1454
+ "grad_norm": 0.774435592352755,
1455
+ "learning_rate": 2.222222222222222e-06,
1456
+ "loss": 0.0861,
1457
+ "mean_token_accuracy": 0.965322732925415,
1458
+ "num_tokens": 3138593.0,
1459
+ "step": 161
1460
+ },
1461
+ {
1462
+ "epoch": 2.7,
1463
+ "grad_norm": 0.8708493282032755,
1464
+ "learning_rate": 2.1111111111111114e-06,
1465
+ "loss": 0.0984,
1466
+ "mean_token_accuracy": 0.963320791721344,
1467
+ "num_tokens": 3157750.0,
1468
+ "step": 162
1469
+ },
1470
+ {
1471
+ "epoch": 2.716666666666667,
1472
+ "grad_norm": 0.6844114412472727,
1473
+ "learning_rate": 2.0000000000000003e-06,
1474
+ "loss": 0.0774,
1475
+ "mean_token_accuracy": 0.9710574746131897,
1476
+ "num_tokens": 3177887.0,
1477
+ "step": 163
1478
+ },
1479
+ {
1480
+ "epoch": 2.7333333333333334,
1481
+ "grad_norm": 0.8269947045633131,
1482
+ "learning_rate": 1.888888888888889e-06,
1483
+ "loss": 0.0966,
1484
+ "mean_token_accuracy": 0.9629047513008118,
1485
+ "num_tokens": 3197305.0,
1486
+ "step": 164
1487
+ },
1488
+ {
1489
+ "epoch": 2.75,
1490
+ "grad_norm": 0.9352308958030469,
1491
+ "learning_rate": 1.777777777777778e-06,
1492
+ "loss": 0.097,
1493
+ "mean_token_accuracy": 0.9620761871337891,
1494
+ "num_tokens": 3216586.0,
1495
+ "step": 165
1496
+ },
1497
+ {
1498
+ "epoch": 2.7666666666666666,
1499
+ "grad_norm": 0.7621362303112271,
1500
+ "learning_rate": 1.6666666666666667e-06,
1501
+ "loss": 0.0907,
1502
+ "mean_token_accuracy": 0.9662196636199951,
1503
+ "num_tokens": 3235533.0,
1504
+ "step": 166
1505
+ },
1506
+ {
1507
+ "epoch": 2.783333333333333,
1508
+ "grad_norm": 0.960964098507404,
1509
+ "learning_rate": 1.5555555555555558e-06,
1510
+ "loss": 0.1011,
1511
+ "mean_token_accuracy": 0.9637789130210876,
1512
+ "num_tokens": 3253955.0,
1513
+ "step": 167
1514
+ },
1515
+ {
1516
+ "epoch": 2.8,
1517
+ "grad_norm": 0.834114847730771,
1518
+ "learning_rate": 1.4444444444444445e-06,
1519
+ "loss": 0.0945,
1520
+ "mean_token_accuracy": 0.9648138880729675,
1521
+ "num_tokens": 3272890.0,
1522
+ "step": 168
1523
+ },
1524
+ {
1525
+ "epoch": 2.8166666666666664,
1526
+ "grad_norm": 0.7527900787887315,
1527
+ "learning_rate": 1.3333333333333334e-06,
1528
+ "loss": 0.0856,
1529
+ "mean_token_accuracy": 0.9682297110557556,
1530
+ "num_tokens": 3291832.0,
1531
+ "step": 169
1532
+ },
1533
+ {
1534
+ "epoch": 2.8333333333333335,
1535
+ "grad_norm": 0.962657962120987,
1536
+ "learning_rate": 1.2222222222222223e-06,
1537
+ "loss": 0.1053,
1538
+ "mean_token_accuracy": 0.9603788256645203,
1539
+ "num_tokens": 3310072.0,
1540
+ "step": 170
1541
+ },
1542
+ {
1543
+ "epoch": 2.85,
1544
+ "grad_norm": 0.6521937551649634,
1545
+ "learning_rate": 1.111111111111111e-06,
1546
+ "loss": 0.0754,
1547
+ "mean_token_accuracy": 0.9735506772994995,
1548
+ "num_tokens": 3329622.0,
1549
+ "step": 171
1550
+ },
1551
+ {
1552
+ "epoch": 2.8666666666666667,
1553
+ "grad_norm": 0.8085295318281304,
1554
+ "learning_rate": 1.0000000000000002e-06,
1555
+ "loss": 0.0851,
1556
+ "mean_token_accuracy": 0.96629399061203,
1557
+ "num_tokens": 3348763.0,
1558
+ "step": 172
1559
+ },
1560
+ {
1561
+ "epoch": 2.8833333333333333,
1562
+ "grad_norm": 0.8908320452034533,
1563
+ "learning_rate": 8.88888888888889e-07,
1564
+ "loss": 0.0935,
1565
+ "mean_token_accuracy": 0.9675348401069641,
1566
+ "num_tokens": 3367256.0,
1567
+ "step": 173
1568
+ },
1569
+ {
1570
+ "epoch": 2.9,
1571
+ "grad_norm": 0.7445211886068831,
1572
+ "learning_rate": 7.777777777777779e-07,
1573
+ "loss": 0.0855,
1574
+ "mean_token_accuracy": 0.968561053276062,
1575
+ "num_tokens": 3386924.0,
1576
+ "step": 174
1577
+ },
1578
+ {
1579
+ "epoch": 2.9166666666666665,
1580
+ "grad_norm": 0.8905272321287844,
1581
+ "learning_rate": 6.666666666666667e-07,
1582
+ "loss": 0.0945,
1583
+ "mean_token_accuracy": 0.9635922312736511,
1584
+ "num_tokens": 3405338.0,
1585
+ "step": 175
1586
+ },
1587
+ {
1588
+ "epoch": 2.9333333333333336,
1589
+ "grad_norm": 0.884095334873471,
1590
+ "learning_rate": 5.555555555555555e-07,
1591
+ "loss": 0.1016,
1592
+ "mean_token_accuracy": 0.9620562791824341,
1593
+ "num_tokens": 3424120.0,
1594
+ "step": 176
1595
+ },
1596
+ {
1597
+ "epoch": 2.95,
1598
+ "grad_norm": 0.9696647110949745,
1599
+ "learning_rate": 4.444444444444445e-07,
1600
+ "loss": 0.1085,
1601
+ "mean_token_accuracy": 0.9581360220909119,
1602
+ "num_tokens": 3442456.0,
1603
+ "step": 177
1604
+ },
1605
+ {
1606
+ "epoch": 2.966666666666667,
1607
+ "grad_norm": 0.8575382869374056,
1608
+ "learning_rate": 3.3333333333333335e-07,
1609
+ "loss": 0.0944,
1610
+ "mean_token_accuracy": 0.9630635380744934,
1611
+ "num_tokens": 3461044.0,
1612
+ "step": 178
1613
+ },
1614
+ {
1615
+ "epoch": 2.9833333333333334,
1616
+ "grad_norm": 0.8796554050600224,
1617
+ "learning_rate": 2.2222222222222224e-07,
1618
+ "loss": 0.0965,
1619
+ "mean_token_accuracy": 0.9649972319602966,
1620
+ "num_tokens": 3479478.0,
1621
+ "step": 179
1622
+ },
1623
+ {
1624
+ "epoch": 3.0,
1625
+ "grad_norm": 0.47092378589770406,
1626
+ "learning_rate": 1.1111111111111112e-07,
1627
+ "loss": 0.0489,
1628
+ "mean_token_accuracy": 0.9833430051803589,
1629
+ "num_tokens": 3496156.0,
1630
+ "step": 180
1631
+ }
1632
+ ],
1633
+ "logging_steps": 1,
1634
+ "max_steps": 180,
1635
+ "num_input_tokens_seen": 0,
1636
+ "num_train_epochs": 3,
1637
+ "save_steps": 500,
1638
+ "stateful_callbacks": {
1639
+ "TrainerControl": {
1640
+ "args": {
1641
+ "should_epoch_stop": false,
1642
+ "should_evaluate": false,
1643
+ "should_log": false,
1644
+ "should_save": true,
1645
+ "should_training_stop": true
1646
+ },
1647
+ "attributes": {}
1648
+ }
1649
+ },
1650
+ "total_flos": 8670117072896.0,
1651
+ "train_batch_size": 4,
1652
+ "trial_name": null,
1653
+ "trial_params": null
1654
+ }
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1f141e72181af549d69af4737ab5e7b06a325933960170588b4ab03a57f1cc75
3
+ size 7032
vocab.json ADDED
The diff for this file is too large to render. See raw diff