ieiei commited on
Commit
6b46a67
1 Parent(s): 4bd3b32

Upload folder using huggingface_hub

Browse files
config.json ADDED
@@ -0,0 +1,28 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "collective-v0.1-chinese-roleplay-8b",
3
+ "architectures": [
4
+ "LlamaForCausalLM"
5
+ ],
6
+ "attention_bias": false,
7
+ "attention_dropout": 0.0,
8
+ "bos_token_id": 128000,
9
+ "eos_token_id": 128009,
10
+ "hidden_act": "silu",
11
+ "hidden_size": 4096,
12
+ "initializer_range": 0.02,
13
+ "intermediate_size": 14336,
14
+ "max_position_embeddings": 8192,
15
+ "model_type": "llama",
16
+ "num_attention_heads": 32,
17
+ "num_hidden_layers": 32,
18
+ "num_key_value_heads": 8,
19
+ "pretraining_tp": 1,
20
+ "rms_norm_eps": 1e-05,
21
+ "rope_scaling": null,
22
+ "rope_theta": 500000.0,
23
+ "tie_word_embeddings": false,
24
+ "torch_dtype": "float16",
25
+ "transformers_version": "4.40.2",
26
+ "use_cache": false,
27
+ "vocab_size": 128256
28
+ }
generation_config.json ADDED
@@ -0,0 +1,6 @@
 
 
 
 
 
 
 
1
+ {
2
+ "_from_model_config": true,
3
+ "bos_token_id": 128000,
4
+ "eos_token_id": 128009,
5
+ "transformers_version": "4.40.2"
6
+ }
latest ADDED
@@ -0,0 +1 @@
 
 
1
+ global_step2500
model-00001-of-00004.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:3ea3d3ba78467c1b6453df4d41c6ed3a8fa39ab99bfe699019046febbebb8326
3
+ size 4976698592
model-00002-of-00004.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:288cb313ea49abba6c3e5b251babc06a0e2dcd659295a181fcc47a4ec8cfc152
3
+ size 4999802616
model-00003-of-00004.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:89b18e5c88c0c70fd346a5309372fae56e2505a7f98dc3093ab729a443e889bd
3
+ size 4915916080
model-00004-of-00004.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7ed2c759045afdd6ce9aebbf293e751dbb3e2c0b0d13af564156d9e6b9188f99
3
+ size 1168138808
model.safetensors.index.json ADDED
@@ -0,0 +1,298 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "metadata": {
3
+ "total_size": 16060522496
4
+ },
5
+ "weight_map": {
6
+ "lm_head.weight": "model-00004-of-00004.safetensors",
7
+ "model.embed_tokens.weight": "model-00001-of-00004.safetensors",
8
+ "model.layers.0.input_layernorm.weight": "model-00001-of-00004.safetensors",
9
+ "model.layers.0.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
10
+ "model.layers.0.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
11
+ "model.layers.0.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
12
+ "model.layers.0.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
13
+ "model.layers.0.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
14
+ "model.layers.0.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
15
+ "model.layers.0.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
16
+ "model.layers.0.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
17
+ "model.layers.1.input_layernorm.weight": "model-00001-of-00004.safetensors",
18
+ "model.layers.1.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
19
+ "model.layers.1.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
20
+ "model.layers.1.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
21
+ "model.layers.1.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
22
+ "model.layers.1.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
23
+ "model.layers.1.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
24
+ "model.layers.1.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
25
+ "model.layers.1.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
26
+ "model.layers.10.input_layernorm.weight": "model-00002-of-00004.safetensors",
27
+ "model.layers.10.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
28
+ "model.layers.10.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
29
+ "model.layers.10.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
30
+ "model.layers.10.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
31
+ "model.layers.10.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
32
+ "model.layers.10.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
33
+ "model.layers.10.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
34
+ "model.layers.10.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
35
+ "model.layers.11.input_layernorm.weight": "model-00002-of-00004.safetensors",
36
+ "model.layers.11.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
37
+ "model.layers.11.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
38
+ "model.layers.11.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
39
+ "model.layers.11.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
40
+ "model.layers.11.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
41
+ "model.layers.11.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
42
+ "model.layers.11.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
43
+ "model.layers.11.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
44
+ "model.layers.12.input_layernorm.weight": "model-00002-of-00004.safetensors",
45
+ "model.layers.12.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
46
+ "model.layers.12.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
47
+ "model.layers.12.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
48
+ "model.layers.12.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
49
+ "model.layers.12.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
50
+ "model.layers.12.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
51
+ "model.layers.12.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
52
+ "model.layers.12.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
53
+ "model.layers.13.input_layernorm.weight": "model-00002-of-00004.safetensors",
54
+ "model.layers.13.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
55
+ "model.layers.13.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
56
+ "model.layers.13.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
57
+ "model.layers.13.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
58
+ "model.layers.13.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
59
+ "model.layers.13.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
60
+ "model.layers.13.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
61
+ "model.layers.13.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
62
+ "model.layers.14.input_layernorm.weight": "model-00002-of-00004.safetensors",
63
+ "model.layers.14.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
64
+ "model.layers.14.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
65
+ "model.layers.14.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
66
+ "model.layers.14.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
67
+ "model.layers.14.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
68
+ "model.layers.14.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
69
+ "model.layers.14.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
70
+ "model.layers.14.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
71
+ "model.layers.15.input_layernorm.weight": "model-00002-of-00004.safetensors",
72
+ "model.layers.15.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
73
+ "model.layers.15.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
74
+ "model.layers.15.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
75
+ "model.layers.15.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
76
+ "model.layers.15.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
77
+ "model.layers.15.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
78
+ "model.layers.15.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
79
+ "model.layers.15.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
80
+ "model.layers.16.input_layernorm.weight": "model-00002-of-00004.safetensors",
81
+ "model.layers.16.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
82
+ "model.layers.16.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
83
+ "model.layers.16.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
84
+ "model.layers.16.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
85
+ "model.layers.16.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
86
+ "model.layers.16.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
87
+ "model.layers.16.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
88
+ "model.layers.16.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
89
+ "model.layers.17.input_layernorm.weight": "model-00002-of-00004.safetensors",
90
+ "model.layers.17.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
91
+ "model.layers.17.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
92
+ "model.layers.17.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
93
+ "model.layers.17.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
94
+ "model.layers.17.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
95
+ "model.layers.17.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
96
+ "model.layers.17.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
97
+ "model.layers.17.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
98
+ "model.layers.18.input_layernorm.weight": "model-00002-of-00004.safetensors",
99
+ "model.layers.18.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
100
+ "model.layers.18.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
101
+ "model.layers.18.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
102
+ "model.layers.18.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
103
+ "model.layers.18.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
104
+ "model.layers.18.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
105
+ "model.layers.18.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
106
+ "model.layers.18.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
107
+ "model.layers.19.input_layernorm.weight": "model-00002-of-00004.safetensors",
108
+ "model.layers.19.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
109
+ "model.layers.19.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
110
+ "model.layers.19.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
111
+ "model.layers.19.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
112
+ "model.layers.19.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
113
+ "model.layers.19.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
114
+ "model.layers.19.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
115
+ "model.layers.19.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
116
+ "model.layers.2.input_layernorm.weight": "model-00001-of-00004.safetensors",
117
+ "model.layers.2.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
118
+ "model.layers.2.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
119
+ "model.layers.2.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
120
+ "model.layers.2.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
121
+ "model.layers.2.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
122
+ "model.layers.2.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
123
+ "model.layers.2.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
124
+ "model.layers.2.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
125
+ "model.layers.20.input_layernorm.weight": "model-00003-of-00004.safetensors",
126
+ "model.layers.20.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
127
+ "model.layers.20.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
128
+ "model.layers.20.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
129
+ "model.layers.20.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
130
+ "model.layers.20.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
131
+ "model.layers.20.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
132
+ "model.layers.20.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
133
+ "model.layers.20.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
134
+ "model.layers.21.input_layernorm.weight": "model-00003-of-00004.safetensors",
135
+ "model.layers.21.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
136
+ "model.layers.21.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
137
+ "model.layers.21.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
138
+ "model.layers.21.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
139
+ "model.layers.21.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
140
+ "model.layers.21.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
141
+ "model.layers.21.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
142
+ "model.layers.21.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
143
+ "model.layers.22.input_layernorm.weight": "model-00003-of-00004.safetensors",
144
+ "model.layers.22.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
145
+ "model.layers.22.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
146
+ "model.layers.22.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
147
+ "model.layers.22.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
148
+ "model.layers.22.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
149
+ "model.layers.22.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
150
+ "model.layers.22.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
151
+ "model.layers.22.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
152
+ "model.layers.23.input_layernorm.weight": "model-00003-of-00004.safetensors",
153
+ "model.layers.23.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
154
+ "model.layers.23.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
155
+ "model.layers.23.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
156
+ "model.layers.23.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
157
+ "model.layers.23.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
158
+ "model.layers.23.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
159
+ "model.layers.23.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
160
+ "model.layers.23.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
161
+ "model.layers.24.input_layernorm.weight": "model-00003-of-00004.safetensors",
162
+ "model.layers.24.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
163
+ "model.layers.24.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
164
+ "model.layers.24.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
165
+ "model.layers.24.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
166
+ "model.layers.24.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
167
+ "model.layers.24.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
168
+ "model.layers.24.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
169
+ "model.layers.24.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
170
+ "model.layers.25.input_layernorm.weight": "model-00003-of-00004.safetensors",
171
+ "model.layers.25.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
172
+ "model.layers.25.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
173
+ "model.layers.25.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
174
+ "model.layers.25.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
175
+ "model.layers.25.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
176
+ "model.layers.25.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
177
+ "model.layers.25.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
178
+ "model.layers.25.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
179
+ "model.layers.26.input_layernorm.weight": "model-00003-of-00004.safetensors",
180
+ "model.layers.26.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
181
+ "model.layers.26.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
182
+ "model.layers.26.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
183
+ "model.layers.26.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
184
+ "model.layers.26.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
185
+ "model.layers.26.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
186
+ "model.layers.26.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
187
+ "model.layers.26.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
188
+ "model.layers.27.input_layernorm.weight": "model-00003-of-00004.safetensors",
189
+ "model.layers.27.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
190
+ "model.layers.27.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
191
+ "model.layers.27.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
192
+ "model.layers.27.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
193
+ "model.layers.27.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
194
+ "model.layers.27.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
195
+ "model.layers.27.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
196
+ "model.layers.27.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
197
+ "model.layers.28.input_layernorm.weight": "model-00003-of-00004.safetensors",
198
+ "model.layers.28.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
199
+ "model.layers.28.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
200
+ "model.layers.28.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
201
+ "model.layers.28.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
202
+ "model.layers.28.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
203
+ "model.layers.28.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
204
+ "model.layers.28.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
205
+ "model.layers.28.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
206
+ "model.layers.29.input_layernorm.weight": "model-00003-of-00004.safetensors",
207
+ "model.layers.29.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
208
+ "model.layers.29.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
209
+ "model.layers.29.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
210
+ "model.layers.29.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
211
+ "model.layers.29.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
212
+ "model.layers.29.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
213
+ "model.layers.29.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
214
+ "model.layers.29.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
215
+ "model.layers.3.input_layernorm.weight": "model-00001-of-00004.safetensors",
216
+ "model.layers.3.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
217
+ "model.layers.3.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
218
+ "model.layers.3.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
219
+ "model.layers.3.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
220
+ "model.layers.3.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
221
+ "model.layers.3.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
222
+ "model.layers.3.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
223
+ "model.layers.3.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
224
+ "model.layers.30.input_layernorm.weight": "model-00003-of-00004.safetensors",
225
+ "model.layers.30.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
226
+ "model.layers.30.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
227
+ "model.layers.30.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
228
+ "model.layers.30.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
229
+ "model.layers.30.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
230
+ "model.layers.30.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
231
+ "model.layers.30.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
232
+ "model.layers.30.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
233
+ "model.layers.31.input_layernorm.weight": "model-00004-of-00004.safetensors",
234
+ "model.layers.31.mlp.down_proj.weight": "model-00004-of-00004.safetensors",
235
+ "model.layers.31.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
236
+ "model.layers.31.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
237
+ "model.layers.31.post_attention_layernorm.weight": "model-00004-of-00004.safetensors",
238
+ "model.layers.31.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
239
+ "model.layers.31.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
240
+ "model.layers.31.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
241
+ "model.layers.31.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
242
+ "model.layers.4.input_layernorm.weight": "model-00001-of-00004.safetensors",
243
+ "model.layers.4.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
244
+ "model.layers.4.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
245
+ "model.layers.4.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
246
+ "model.layers.4.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
247
+ "model.layers.4.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
248
+ "model.layers.4.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
249
+ "model.layers.4.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
250
+ "model.layers.4.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
251
+ "model.layers.5.input_layernorm.weight": "model-00001-of-00004.safetensors",
252
+ "model.layers.5.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
253
+ "model.layers.5.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
254
+ "model.layers.5.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
255
+ "model.layers.5.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
256
+ "model.layers.5.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
257
+ "model.layers.5.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
258
+ "model.layers.5.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
259
+ "model.layers.5.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
260
+ "model.layers.6.input_layernorm.weight": "model-00001-of-00004.safetensors",
261
+ "model.layers.6.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
262
+ "model.layers.6.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
263
+ "model.layers.6.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
264
+ "model.layers.6.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
265
+ "model.layers.6.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
266
+ "model.layers.6.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
267
+ "model.layers.6.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
268
+ "model.layers.6.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
269
+ "model.layers.7.input_layernorm.weight": "model-00001-of-00004.safetensors",
270
+ "model.layers.7.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
271
+ "model.layers.7.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
272
+ "model.layers.7.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
273
+ "model.layers.7.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
274
+ "model.layers.7.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
275
+ "model.layers.7.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
276
+ "model.layers.7.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
277
+ "model.layers.7.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
278
+ "model.layers.8.input_layernorm.weight": "model-00001-of-00004.safetensors",
279
+ "model.layers.8.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
280
+ "model.layers.8.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
281
+ "model.layers.8.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
282
+ "model.layers.8.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
283
+ "model.layers.8.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
284
+ "model.layers.8.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
285
+ "model.layers.8.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
286
+ "model.layers.8.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
287
+ "model.layers.9.input_layernorm.weight": "model-00002-of-00004.safetensors",
288
+ "model.layers.9.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
289
+ "model.layers.9.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
290
+ "model.layers.9.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
291
+ "model.layers.9.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
292
+ "model.layers.9.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
293
+ "model.layers.9.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
294
+ "model.layers.9.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
295
+ "model.layers.9.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
296
+ "model.norm.weight": "model-00004-of-00004.safetensors"
297
+ }
298
+ }
rng_state_0.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9c49abc3bdedbec1fc8e1028ef422150f19ee7470d7b542e1ad8869fc044d2af
3
+ size 15984
rng_state_1.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:df12ca4106ff0831785a55b5da88f6c86f6f67bd3d09b2dced4f20b539b14f72
3
+ size 15984
rng_state_2.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:05fc0786faff729a3a1582f98b806b68d4f0b76aebb25cbad4431b73176b11c1
3
+ size 15984
rng_state_3.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a3117e1218a2dd3f7f8c516a840af48f6b93660d852cca124269f78c21f8577c
3
+ size 15984
rng_state_4.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:cdaa30c82476bf6a65e4eb9ca2ae7b95f1b38f41a6f5b2f1cbdda9af86a4a7a0
3
+ size 15984
rng_state_5.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:09cdde6931807139efa184e8a98108b74bb05730bc511336966b254b68dc93ee
3
+ size 15984
rng_state_6.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:8a2268136932c55b3857d38c7cf3fc4bd3cdad532c156b9addebc6d26374374a
3
+ size 15984
rng_state_7.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:56cd9a502015b79e0ab94c92a04bd96c99aaf79ef8d64bf81d81eb702c10c2a8
3
+ size 15984
scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e83649e8ab139de24dbe5eb9bccdeb154d16fbc40548ad16b8a8aefa2273ffb7
3
+ size 1064
special_tokens_map.json ADDED
@@ -0,0 +1,23 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bos_token": {
3
+ "content": "<|begin_of_text|>",
4
+ "lstrip": false,
5
+ "normalized": false,
6
+ "rstrip": false,
7
+ "single_word": false
8
+ },
9
+ "eos_token": {
10
+ "content": "<|eot_id|>",
11
+ "lstrip": false,
12
+ "normalized": false,
13
+ "rstrip": false,
14
+ "single_word": false
15
+ },
16
+ "pad_token": {
17
+ "content": "<|eot_id|>",
18
+ "lstrip": false,
19
+ "normalized": false,
20
+ "rstrip": false,
21
+ "single_word": false
22
+ }
23
+ }
tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
tokenizer_config.json ADDED
@@ -0,0 +1,2065 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "added_tokens_decoder": {
3
+ "128000": {
4
+ "content": "<|begin_of_text|>",
5
+ "lstrip": false,
6
+ "normalized": false,
7
+ "rstrip": false,
8
+ "single_word": false,
9
+ "special": true
10
+ },
11
+ "128001": {
12
+ "content": "<|end_of_text|>",
13
+ "lstrip": false,
14
+ "normalized": false,
15
+ "rstrip": false,
16
+ "single_word": false,
17
+ "special": true
18
+ },
19
+ "128002": {
20
+ "content": "<|reserved_special_token_0|>",
21
+ "lstrip": false,
22
+ "normalized": false,
23
+ "rstrip": false,
24
+ "single_word": false,
25
+ "special": true
26
+ },
27
+ "128003": {
28
+ "content": "<|reserved_special_token_1|>",
29
+ "lstrip": false,
30
+ "normalized": false,
31
+ "rstrip": false,
32
+ "single_word": false,
33
+ "special": true
34
+ },
35
+ "128004": {
36
+ "content": "<|reserved_special_token_2|>",
37
+ "lstrip": false,
38
+ "normalized": false,
39
+ "rstrip": false,
40
+ "single_word": false,
41
+ "special": true
42
+ },
43
+ "128005": {
44
+ "content": "<|reserved_special_token_3|>",
45
+ "lstrip": false,
46
+ "normalized": false,
47
+ "rstrip": false,
48
+ "single_word": false,
49
+ "special": true
50
+ },
51
+ "128006": {
52
+ "content": "<|start_header_id|>",
53
+ "lstrip": false,
54
+ "normalized": false,
55
+ "rstrip": false,
56
+ "single_word": false,
57
+ "special": true
58
+ },
59
+ "128007": {
60
+ "content": "<|end_header_id|>",
61
+ "lstrip": false,
62
+ "normalized": false,
63
+ "rstrip": false,
64
+ "single_word": false,
65
+ "special": true
66
+ },
67
+ "128008": {
68
+ "content": "<|reserved_special_token_4|>",
69
+ "lstrip": false,
70
+ "normalized": false,
71
+ "rstrip": false,
72
+ "single_word": false,
73
+ "special": true
74
+ },
75
+ "128009": {
76
+ "content": "<|eot_id|>",
77
+ "lstrip": false,
78
+ "normalized": false,
79
+ "rstrip": false,
80
+ "single_word": false,
81
+ "special": true
82
+ },
83
+ "128010": {
84
+ "content": "<|reserved_special_token_5|>",
85
+ "lstrip": false,
86
+ "normalized": false,
87
+ "rstrip": false,
88
+ "single_word": false,
89
+ "special": true
90
+ },
91
+ "128011": {
92
+ "content": "<|reserved_special_token_6|>",
93
+ "lstrip": false,
94
+ "normalized": false,
95
+ "rstrip": false,
96
+ "single_word": false,
97
+ "special": true
98
+ },
99
+ "128012": {
100
+ "content": "<|reserved_special_token_7|>",
101
+ "lstrip": false,
102
+ "normalized": false,
103
+ "rstrip": false,
104
+ "single_word": false,
105
+ "special": true
106
+ },
107
+ "128013": {
108
+ "content": "<|reserved_special_token_8|>",
109
+ "lstrip": false,
110
+ "normalized": false,
111
+ "rstrip": false,
112
+ "single_word": false,
113
+ "special": true
114
+ },
115
+ "128014": {
116
+ "content": "<|reserved_special_token_9|>",
117
+ "lstrip": false,
118
+ "normalized": false,
119
+ "rstrip": false,
120
+ "single_word": false,
121
+ "special": true
122
+ },
123
+ "128015": {
124
+ "content": "<|reserved_special_token_10|>",
125
+ "lstrip": false,
126
+ "normalized": false,
127
+ "rstrip": false,
128
+ "single_word": false,
129
+ "special": true
130
+ },
131
+ "128016": {
132
+ "content": "<|reserved_special_token_11|>",
133
+ "lstrip": false,
134
+ "normalized": false,
135
+ "rstrip": false,
136
+ "single_word": false,
137
+ "special": true
138
+ },
139
+ "128017": {
140
+ "content": "<|reserved_special_token_12|>",
141
+ "lstrip": false,
142
+ "normalized": false,
143
+ "rstrip": false,
144
+ "single_word": false,
145
+ "special": true
146
+ },
147
+ "128018": {
148
+ "content": "<|reserved_special_token_13|>",
149
+ "lstrip": false,
150
+ "normalized": false,
151
+ "rstrip": false,
152
+ "single_word": false,
153
+ "special": true
154
+ },
155
+ "128019": {
156
+ "content": "<|reserved_special_token_14|>",
157
+ "lstrip": false,
158
+ "normalized": false,
159
+ "rstrip": false,
160
+ "single_word": false,
161
+ "special": true
162
+ },
163
+ "128020": {
164
+ "content": "<|reserved_special_token_15|>",
165
+ "lstrip": false,
166
+ "normalized": false,
167
+ "rstrip": false,
168
+ "single_word": false,
169
+ "special": true
170
+ },
171
+ "128021": {
172
+ "content": "<|reserved_special_token_16|>",
173
+ "lstrip": false,
174
+ "normalized": false,
175
+ "rstrip": false,
176
+ "single_word": false,
177
+ "special": true
178
+ },
179
+ "128022": {
180
+ "content": "<|reserved_special_token_17|>",
181
+ "lstrip": false,
182
+ "normalized": false,
183
+ "rstrip": false,
184
+ "single_word": false,
185
+ "special": true
186
+ },
187
+ "128023": {
188
+ "content": "<|reserved_special_token_18|>",
189
+ "lstrip": false,
190
+ "normalized": false,
191
+ "rstrip": false,
192
+ "single_word": false,
193
+ "special": true
194
+ },
195
+ "128024": {
196
+ "content": "<|reserved_special_token_19|>",
197
+ "lstrip": false,
198
+ "normalized": false,
199
+ "rstrip": false,
200
+ "single_word": false,
201
+ "special": true
202
+ },
203
+ "128025": {
204
+ "content": "<|reserved_special_token_20|>",
205
+ "lstrip": false,
206
+ "normalized": false,
207
+ "rstrip": false,
208
+ "single_word": false,
209
+ "special": true
210
+ },
211
+ "128026": {
212
+ "content": "<|reserved_special_token_21|>",
213
+ "lstrip": false,
214
+ "normalized": false,
215
+ "rstrip": false,
216
+ "single_word": false,
217
+ "special": true
218
+ },
219
+ "128027": {
220
+ "content": "<|reserved_special_token_22|>",
221
+ "lstrip": false,
222
+ "normalized": false,
223
+ "rstrip": false,
224
+ "single_word": false,
225
+ "special": true
226
+ },
227
+ "128028": {
228
+ "content": "<|reserved_special_token_23|>",
229
+ "lstrip": false,
230
+ "normalized": false,
231
+ "rstrip": false,
232
+ "single_word": false,
233
+ "special": true
234
+ },
235
+ "128029": {
236
+ "content": "<|reserved_special_token_24|>",
237
+ "lstrip": false,
238
+ "normalized": false,
239
+ "rstrip": false,
240
+ "single_word": false,
241
+ "special": true
242
+ },
243
+ "128030": {
244
+ "content": "<|reserved_special_token_25|>",
245
+ "lstrip": false,
246
+ "normalized": false,
247
+ "rstrip": false,
248
+ "single_word": false,
249
+ "special": true
250
+ },
251
+ "128031": {
252
+ "content": "<|reserved_special_token_26|>",
253
+ "lstrip": false,
254
+ "normalized": false,
255
+ "rstrip": false,
256
+ "single_word": false,
257
+ "special": true
258
+ },
259
+ "128032": {
260
+ "content": "<|reserved_special_token_27|>",
261
+ "lstrip": false,
262
+ "normalized": false,
263
+ "rstrip": false,
264
+ "single_word": false,
265
+ "special": true
266
+ },
267
+ "128033": {
268
+ "content": "<|reserved_special_token_28|>",
269
+ "lstrip": false,
270
+ "normalized": false,
271
+ "rstrip": false,
272
+ "single_word": false,
273
+ "special": true
274
+ },
275
+ "128034": {
276
+ "content": "<|reserved_special_token_29|>",
277
+ "lstrip": false,
278
+ "normalized": false,
279
+ "rstrip": false,
280
+ "single_word": false,
281
+ "special": true
282
+ },
283
+ "128035": {
284
+ "content": "<|reserved_special_token_30|>",
285
+ "lstrip": false,
286
+ "normalized": false,
287
+ "rstrip": false,
288
+ "single_word": false,
289
+ "special": true
290
+ },
291
+ "128036": {
292
+ "content": "<|reserved_special_token_31|>",
293
+ "lstrip": false,
294
+ "normalized": false,
295
+ "rstrip": false,
296
+ "single_word": false,
297
+ "special": true
298
+ },
299
+ "128037": {
300
+ "content": "<|reserved_special_token_32|>",
301
+ "lstrip": false,
302
+ "normalized": false,
303
+ "rstrip": false,
304
+ "single_word": false,
305
+ "special": true
306
+ },
307
+ "128038": {
308
+ "content": "<|reserved_special_token_33|>",
309
+ "lstrip": false,
310
+ "normalized": false,
311
+ "rstrip": false,
312
+ "single_word": false,
313
+ "special": true
314
+ },
315
+ "128039": {
316
+ "content": "<|reserved_special_token_34|>",
317
+ "lstrip": false,
318
+ "normalized": false,
319
+ "rstrip": false,
320
+ "single_word": false,
321
+ "special": true
322
+ },
323
+ "128040": {
324
+ "content": "<|reserved_special_token_35|>",
325
+ "lstrip": false,
326
+ "normalized": false,
327
+ "rstrip": false,
328
+ "single_word": false,
329
+ "special": true
330
+ },
331
+ "128041": {
332
+ "content": "<|reserved_special_token_36|>",
333
+ "lstrip": false,
334
+ "normalized": false,
335
+ "rstrip": false,
336
+ "single_word": false,
337
+ "special": true
338
+ },
339
+ "128042": {
340
+ "content": "<|reserved_special_token_37|>",
341
+ "lstrip": false,
342
+ "normalized": false,
343
+ "rstrip": false,
344
+ "single_word": false,
345
+ "special": true
346
+ },
347
+ "128043": {
348
+ "content": "<|reserved_special_token_38|>",
349
+ "lstrip": false,
350
+ "normalized": false,
351
+ "rstrip": false,
352
+ "single_word": false,
353
+ "special": true
354
+ },
355
+ "128044": {
356
+ "content": "<|reserved_special_token_39|>",
357
+ "lstrip": false,
358
+ "normalized": false,
359
+ "rstrip": false,
360
+ "single_word": false,
361
+ "special": true
362
+ },
363
+ "128045": {
364
+ "content": "<|reserved_special_token_40|>",
365
+ "lstrip": false,
366
+ "normalized": false,
367
+ "rstrip": false,
368
+ "single_word": false,
369
+ "special": true
370
+ },
371
+ "128046": {
372
+ "content": "<|reserved_special_token_41|>",
373
+ "lstrip": false,
374
+ "normalized": false,
375
+ "rstrip": false,
376
+ "single_word": false,
377
+ "special": true
378
+ },
379
+ "128047": {
380
+ "content": "<|reserved_special_token_42|>",
381
+ "lstrip": false,
382
+ "normalized": false,
383
+ "rstrip": false,
384
+ "single_word": false,
385
+ "special": true
386
+ },
387
+ "128048": {
388
+ "content": "<|reserved_special_token_43|>",
389
+ "lstrip": false,
390
+ "normalized": false,
391
+ "rstrip": false,
392
+ "single_word": false,
393
+ "special": true
394
+ },
395
+ "128049": {
396
+ "content": "<|reserved_special_token_44|>",
397
+ "lstrip": false,
398
+ "normalized": false,
399
+ "rstrip": false,
400
+ "single_word": false,
401
+ "special": true
402
+ },
403
+ "128050": {
404
+ "content": "<|reserved_special_token_45|>",
405
+ "lstrip": false,
406
+ "normalized": false,
407
+ "rstrip": false,
408
+ "single_word": false,
409
+ "special": true
410
+ },
411
+ "128051": {
412
+ "content": "<|reserved_special_token_46|>",
413
+ "lstrip": false,
414
+ "normalized": false,
415
+ "rstrip": false,
416
+ "single_word": false,
417
+ "special": true
418
+ },
419
+ "128052": {
420
+ "content": "<|reserved_special_token_47|>",
421
+ "lstrip": false,
422
+ "normalized": false,
423
+ "rstrip": false,
424
+ "single_word": false,
425
+ "special": true
426
+ },
427
+ "128053": {
428
+ "content": "<|reserved_special_token_48|>",
429
+ "lstrip": false,
430
+ "normalized": false,
431
+ "rstrip": false,
432
+ "single_word": false,
433
+ "special": true
434
+ },
435
+ "128054": {
436
+ "content": "<|reserved_special_token_49|>",
437
+ "lstrip": false,
438
+ "normalized": false,
439
+ "rstrip": false,
440
+ "single_word": false,
441
+ "special": true
442
+ },
443
+ "128055": {
444
+ "content": "<|reserved_special_token_50|>",
445
+ "lstrip": false,
446
+ "normalized": false,
447
+ "rstrip": false,
448
+ "single_word": false,
449
+ "special": true
450
+ },
451
+ "128056": {
452
+ "content": "<|reserved_special_token_51|>",
453
+ "lstrip": false,
454
+ "normalized": false,
455
+ "rstrip": false,
456
+ "single_word": false,
457
+ "special": true
458
+ },
459
+ "128057": {
460
+ "content": "<|reserved_special_token_52|>",
461
+ "lstrip": false,
462
+ "normalized": false,
463
+ "rstrip": false,
464
+ "single_word": false,
465
+ "special": true
466
+ },
467
+ "128058": {
468
+ "content": "<|reserved_special_token_53|>",
469
+ "lstrip": false,
470
+ "normalized": false,
471
+ "rstrip": false,
472
+ "single_word": false,
473
+ "special": true
474
+ },
475
+ "128059": {
476
+ "content": "<|reserved_special_token_54|>",
477
+ "lstrip": false,
478
+ "normalized": false,
479
+ "rstrip": false,
480
+ "single_word": false,
481
+ "special": true
482
+ },
483
+ "128060": {
484
+ "content": "<|reserved_special_token_55|>",
485
+ "lstrip": false,
486
+ "normalized": false,
487
+ "rstrip": false,
488
+ "single_word": false,
489
+ "special": true
490
+ },
491
+ "128061": {
492
+ "content": "<|reserved_special_token_56|>",
493
+ "lstrip": false,
494
+ "normalized": false,
495
+ "rstrip": false,
496
+ "single_word": false,
497
+ "special": true
498
+ },
499
+ "128062": {
500
+ "content": "<|reserved_special_token_57|>",
501
+ "lstrip": false,
502
+ "normalized": false,
503
+ "rstrip": false,
504
+ "single_word": false,
505
+ "special": true
506
+ },
507
+ "128063": {
508
+ "content": "<|reserved_special_token_58|>",
509
+ "lstrip": false,
510
+ "normalized": false,
511
+ "rstrip": false,
512
+ "single_word": false,
513
+ "special": true
514
+ },
515
+ "128064": {
516
+ "content": "<|reserved_special_token_59|>",
517
+ "lstrip": false,
518
+ "normalized": false,
519
+ "rstrip": false,
520
+ "single_word": false,
521
+ "special": true
522
+ },
523
+ "128065": {
524
+ "content": "<|reserved_special_token_60|>",
525
+ "lstrip": false,
526
+ "normalized": false,
527
+ "rstrip": false,
528
+ "single_word": false,
529
+ "special": true
530
+ },
531
+ "128066": {
532
+ "content": "<|reserved_special_token_61|>",
533
+ "lstrip": false,
534
+ "normalized": false,
535
+ "rstrip": false,
536
+ "single_word": false,
537
+ "special": true
538
+ },
539
+ "128067": {
540
+ "content": "<|reserved_special_token_62|>",
541
+ "lstrip": false,
542
+ "normalized": false,
543
+ "rstrip": false,
544
+ "single_word": false,
545
+ "special": true
546
+ },
547
+ "128068": {
548
+ "content": "<|reserved_special_token_63|>",
549
+ "lstrip": false,
550
+ "normalized": false,
551
+ "rstrip": false,
552
+ "single_word": false,
553
+ "special": true
554
+ },
555
+ "128069": {
556
+ "content": "<|reserved_special_token_64|>",
557
+ "lstrip": false,
558
+ "normalized": false,
559
+ "rstrip": false,
560
+ "single_word": false,
561
+ "special": true
562
+ },
563
+ "128070": {
564
+ "content": "<|reserved_special_token_65|>",
565
+ "lstrip": false,
566
+ "normalized": false,
567
+ "rstrip": false,
568
+ "single_word": false,
569
+ "special": true
570
+ },
571
+ "128071": {
572
+ "content": "<|reserved_special_token_66|>",
573
+ "lstrip": false,
574
+ "normalized": false,
575
+ "rstrip": false,
576
+ "single_word": false,
577
+ "special": true
578
+ },
579
+ "128072": {
580
+ "content": "<|reserved_special_token_67|>",
581
+ "lstrip": false,
582
+ "normalized": false,
583
+ "rstrip": false,
584
+ "single_word": false,
585
+ "special": true
586
+ },
587
+ "128073": {
588
+ "content": "<|reserved_special_token_68|>",
589
+ "lstrip": false,
590
+ "normalized": false,
591
+ "rstrip": false,
592
+ "single_word": false,
593
+ "special": true
594
+ },
595
+ "128074": {
596
+ "content": "<|reserved_special_token_69|>",
597
+ "lstrip": false,
598
+ "normalized": false,
599
+ "rstrip": false,
600
+ "single_word": false,
601
+ "special": true
602
+ },
603
+ "128075": {
604
+ "content": "<|reserved_special_token_70|>",
605
+ "lstrip": false,
606
+ "normalized": false,
607
+ "rstrip": false,
608
+ "single_word": false,
609
+ "special": true
610
+ },
611
+ "128076": {
612
+ "content": "<|reserved_special_token_71|>",
613
+ "lstrip": false,
614
+ "normalized": false,
615
+ "rstrip": false,
616
+ "single_word": false,
617
+ "special": true
618
+ },
619
+ "128077": {
620
+ "content": "<|reserved_special_token_72|>",
621
+ "lstrip": false,
622
+ "normalized": false,
623
+ "rstrip": false,
624
+ "single_word": false,
625
+ "special": true
626
+ },
627
+ "128078": {
628
+ "content": "<|reserved_special_token_73|>",
629
+ "lstrip": false,
630
+ "normalized": false,
631
+ "rstrip": false,
632
+ "single_word": false,
633
+ "special": true
634
+ },
635
+ "128079": {
636
+ "content": "<|reserved_special_token_74|>",
637
+ "lstrip": false,
638
+ "normalized": false,
639
+ "rstrip": false,
640
+ "single_word": false,
641
+ "special": true
642
+ },
643
+ "128080": {
644
+ "content": "<|reserved_special_token_75|>",
645
+ "lstrip": false,
646
+ "normalized": false,
647
+ "rstrip": false,
648
+ "single_word": false,
649
+ "special": true
650
+ },
651
+ "128081": {
652
+ "content": "<|reserved_special_token_76|>",
653
+ "lstrip": false,
654
+ "normalized": false,
655
+ "rstrip": false,
656
+ "single_word": false,
657
+ "special": true
658
+ },
659
+ "128082": {
660
+ "content": "<|reserved_special_token_77|>",
661
+ "lstrip": false,
662
+ "normalized": false,
663
+ "rstrip": false,
664
+ "single_word": false,
665
+ "special": true
666
+ },
667
+ "128083": {
668
+ "content": "<|reserved_special_token_78|>",
669
+ "lstrip": false,
670
+ "normalized": false,
671
+ "rstrip": false,
672
+ "single_word": false,
673
+ "special": true
674
+ },
675
+ "128084": {
676
+ "content": "<|reserved_special_token_79|>",
677
+ "lstrip": false,
678
+ "normalized": false,
679
+ "rstrip": false,
680
+ "single_word": false,
681
+ "special": true
682
+ },
683
+ "128085": {
684
+ "content": "<|reserved_special_token_80|>",
685
+ "lstrip": false,
686
+ "normalized": false,
687
+ "rstrip": false,
688
+ "single_word": false,
689
+ "special": true
690
+ },
691
+ "128086": {
692
+ "content": "<|reserved_special_token_81|>",
693
+ "lstrip": false,
694
+ "normalized": false,
695
+ "rstrip": false,
696
+ "single_word": false,
697
+ "special": true
698
+ },
699
+ "128087": {
700
+ "content": "<|reserved_special_token_82|>",
701
+ "lstrip": false,
702
+ "normalized": false,
703
+ "rstrip": false,
704
+ "single_word": false,
705
+ "special": true
706
+ },
707
+ "128088": {
708
+ "content": "<|reserved_special_token_83|>",
709
+ "lstrip": false,
710
+ "normalized": false,
711
+ "rstrip": false,
712
+ "single_word": false,
713
+ "special": true
714
+ },
715
+ "128089": {
716
+ "content": "<|reserved_special_token_84|>",
717
+ "lstrip": false,
718
+ "normalized": false,
719
+ "rstrip": false,
720
+ "single_word": false,
721
+ "special": true
722
+ },
723
+ "128090": {
724
+ "content": "<|reserved_special_token_85|>",
725
+ "lstrip": false,
726
+ "normalized": false,
727
+ "rstrip": false,
728
+ "single_word": false,
729
+ "special": true
730
+ },
731
+ "128091": {
732
+ "content": "<|reserved_special_token_86|>",
733
+ "lstrip": false,
734
+ "normalized": false,
735
+ "rstrip": false,
736
+ "single_word": false,
737
+ "special": true
738
+ },
739
+ "128092": {
740
+ "content": "<|reserved_special_token_87|>",
741
+ "lstrip": false,
742
+ "normalized": false,
743
+ "rstrip": false,
744
+ "single_word": false,
745
+ "special": true
746
+ },
747
+ "128093": {
748
+ "content": "<|reserved_special_token_88|>",
749
+ "lstrip": false,
750
+ "normalized": false,
751
+ "rstrip": false,
752
+ "single_word": false,
753
+ "special": true
754
+ },
755
+ "128094": {
756
+ "content": "<|reserved_special_token_89|>",
757
+ "lstrip": false,
758
+ "normalized": false,
759
+ "rstrip": false,
760
+ "single_word": false,
761
+ "special": true
762
+ },
763
+ "128095": {
764
+ "content": "<|reserved_special_token_90|>",
765
+ "lstrip": false,
766
+ "normalized": false,
767
+ "rstrip": false,
768
+ "single_word": false,
769
+ "special": true
770
+ },
771
+ "128096": {
772
+ "content": "<|reserved_special_token_91|>",
773
+ "lstrip": false,
774
+ "normalized": false,
775
+ "rstrip": false,
776
+ "single_word": false,
777
+ "special": true
778
+ },
779
+ "128097": {
780
+ "content": "<|reserved_special_token_92|>",
781
+ "lstrip": false,
782
+ "normalized": false,
783
+ "rstrip": false,
784
+ "single_word": false,
785
+ "special": true
786
+ },
787
+ "128098": {
788
+ "content": "<|reserved_special_token_93|>",
789
+ "lstrip": false,
790
+ "normalized": false,
791
+ "rstrip": false,
792
+ "single_word": false,
793
+ "special": true
794
+ },
795
+ "128099": {
796
+ "content": "<|reserved_special_token_94|>",
797
+ "lstrip": false,
798
+ "normalized": false,
799
+ "rstrip": false,
800
+ "single_word": false,
801
+ "special": true
802
+ },
803
+ "128100": {
804
+ "content": "<|reserved_special_token_95|>",
805
+ "lstrip": false,
806
+ "normalized": false,
807
+ "rstrip": false,
808
+ "single_word": false,
809
+ "special": true
810
+ },
811
+ "128101": {
812
+ "content": "<|reserved_special_token_96|>",
813
+ "lstrip": false,
814
+ "normalized": false,
815
+ "rstrip": false,
816
+ "single_word": false,
817
+ "special": true
818
+ },
819
+ "128102": {
820
+ "content": "<|reserved_special_token_97|>",
821
+ "lstrip": false,
822
+ "normalized": false,
823
+ "rstrip": false,
824
+ "single_word": false,
825
+ "special": true
826
+ },
827
+ "128103": {
828
+ "content": "<|reserved_special_token_98|>",
829
+ "lstrip": false,
830
+ "normalized": false,
831
+ "rstrip": false,
832
+ "single_word": false,
833
+ "special": true
834
+ },
835
+ "128104": {
836
+ "content": "<|reserved_special_token_99|>",
837
+ "lstrip": false,
838
+ "normalized": false,
839
+ "rstrip": false,
840
+ "single_word": false,
841
+ "special": true
842
+ },
843
+ "128105": {
844
+ "content": "<|reserved_special_token_100|>",
845
+ "lstrip": false,
846
+ "normalized": false,
847
+ "rstrip": false,
848
+ "single_word": false,
849
+ "special": true
850
+ },
851
+ "128106": {
852
+ "content": "<|reserved_special_token_101|>",
853
+ "lstrip": false,
854
+ "normalized": false,
855
+ "rstrip": false,
856
+ "single_word": false,
857
+ "special": true
858
+ },
859
+ "128107": {
860
+ "content": "<|reserved_special_token_102|>",
861
+ "lstrip": false,
862
+ "normalized": false,
863
+ "rstrip": false,
864
+ "single_word": false,
865
+ "special": true
866
+ },
867
+ "128108": {
868
+ "content": "<|reserved_special_token_103|>",
869
+ "lstrip": false,
870
+ "normalized": false,
871
+ "rstrip": false,
872
+ "single_word": false,
873
+ "special": true
874
+ },
875
+ "128109": {
876
+ "content": "<|reserved_special_token_104|>",
877
+ "lstrip": false,
878
+ "normalized": false,
879
+ "rstrip": false,
880
+ "single_word": false,
881
+ "special": true
882
+ },
883
+ "128110": {
884
+ "content": "<|reserved_special_token_105|>",
885
+ "lstrip": false,
886
+ "normalized": false,
887
+ "rstrip": false,
888
+ "single_word": false,
889
+ "special": true
890
+ },
891
+ "128111": {
892
+ "content": "<|reserved_special_token_106|>",
893
+ "lstrip": false,
894
+ "normalized": false,
895
+ "rstrip": false,
896
+ "single_word": false,
897
+ "special": true
898
+ },
899
+ "128112": {
900
+ "content": "<|reserved_special_token_107|>",
901
+ "lstrip": false,
902
+ "normalized": false,
903
+ "rstrip": false,
904
+ "single_word": false,
905
+ "special": true
906
+ },
907
+ "128113": {
908
+ "content": "<|reserved_special_token_108|>",
909
+ "lstrip": false,
910
+ "normalized": false,
911
+ "rstrip": false,
912
+ "single_word": false,
913
+ "special": true
914
+ },
915
+ "128114": {
916
+ "content": "<|reserved_special_token_109|>",
917
+ "lstrip": false,
918
+ "normalized": false,
919
+ "rstrip": false,
920
+ "single_word": false,
921
+ "special": true
922
+ },
923
+ "128115": {
924
+ "content": "<|reserved_special_token_110|>",
925
+ "lstrip": false,
926
+ "normalized": false,
927
+ "rstrip": false,
928
+ "single_word": false,
929
+ "special": true
930
+ },
931
+ "128116": {
932
+ "content": "<|reserved_special_token_111|>",
933
+ "lstrip": false,
934
+ "normalized": false,
935
+ "rstrip": false,
936
+ "single_word": false,
937
+ "special": true
938
+ },
939
+ "128117": {
940
+ "content": "<|reserved_special_token_112|>",
941
+ "lstrip": false,
942
+ "normalized": false,
943
+ "rstrip": false,
944
+ "single_word": false,
945
+ "special": true
946
+ },
947
+ "128118": {
948
+ "content": "<|reserved_special_token_113|>",
949
+ "lstrip": false,
950
+ "normalized": false,
951
+ "rstrip": false,
952
+ "single_word": false,
953
+ "special": true
954
+ },
955
+ "128119": {
956
+ "content": "<|reserved_special_token_114|>",
957
+ "lstrip": false,
958
+ "normalized": false,
959
+ "rstrip": false,
960
+ "single_word": false,
961
+ "special": true
962
+ },
963
+ "128120": {
964
+ "content": "<|reserved_special_token_115|>",
965
+ "lstrip": false,
966
+ "normalized": false,
967
+ "rstrip": false,
968
+ "single_word": false,
969
+ "special": true
970
+ },
971
+ "128121": {
972
+ "content": "<|reserved_special_token_116|>",
973
+ "lstrip": false,
974
+ "normalized": false,
975
+ "rstrip": false,
976
+ "single_word": false,
977
+ "special": true
978
+ },
979
+ "128122": {
980
+ "content": "<|reserved_special_token_117|>",
981
+ "lstrip": false,
982
+ "normalized": false,
983
+ "rstrip": false,
984
+ "single_word": false,
985
+ "special": true
986
+ },
987
+ "128123": {
988
+ "content": "<|reserved_special_token_118|>",
989
+ "lstrip": false,
990
+ "normalized": false,
991
+ "rstrip": false,
992
+ "single_word": false,
993
+ "special": true
994
+ },
995
+ "128124": {
996
+ "content": "<|reserved_special_token_119|>",
997
+ "lstrip": false,
998
+ "normalized": false,
999
+ "rstrip": false,
1000
+ "single_word": false,
1001
+ "special": true
1002
+ },
1003
+ "128125": {
1004
+ "content": "<|reserved_special_token_120|>",
1005
+ "lstrip": false,
1006
+ "normalized": false,
1007
+ "rstrip": false,
1008
+ "single_word": false,
1009
+ "special": true
1010
+ },
1011
+ "128126": {
1012
+ "content": "<|reserved_special_token_121|>",
1013
+ "lstrip": false,
1014
+ "normalized": false,
1015
+ "rstrip": false,
1016
+ "single_word": false,
1017
+ "special": true
1018
+ },
1019
+ "128127": {
1020
+ "content": "<|reserved_special_token_122|>",
1021
+ "lstrip": false,
1022
+ "normalized": false,
1023
+ "rstrip": false,
1024
+ "single_word": false,
1025
+ "special": true
1026
+ },
1027
+ "128128": {
1028
+ "content": "<|reserved_special_token_123|>",
1029
+ "lstrip": false,
1030
+ "normalized": false,
1031
+ "rstrip": false,
1032
+ "single_word": false,
1033
+ "special": true
1034
+ },
1035
+ "128129": {
1036
+ "content": "<|reserved_special_token_124|>",
1037
+ "lstrip": false,
1038
+ "normalized": false,
1039
+ "rstrip": false,
1040
+ "single_word": false,
1041
+ "special": true
1042
+ },
1043
+ "128130": {
1044
+ "content": "<|reserved_special_token_125|>",
1045
+ "lstrip": false,
1046
+ "normalized": false,
1047
+ "rstrip": false,
1048
+ "single_word": false,
1049
+ "special": true
1050
+ },
1051
+ "128131": {
1052
+ "content": "<|reserved_special_token_126|>",
1053
+ "lstrip": false,
1054
+ "normalized": false,
1055
+ "rstrip": false,
1056
+ "single_word": false,
1057
+ "special": true
1058
+ },
1059
+ "128132": {
1060
+ "content": "<|reserved_special_token_127|>",
1061
+ "lstrip": false,
1062
+ "normalized": false,
1063
+ "rstrip": false,
1064
+ "single_word": false,
1065
+ "special": true
1066
+ },
1067
+ "128133": {
1068
+ "content": "<|reserved_special_token_128|>",
1069
+ "lstrip": false,
1070
+ "normalized": false,
1071
+ "rstrip": false,
1072
+ "single_word": false,
1073
+ "special": true
1074
+ },
1075
+ "128134": {
1076
+ "content": "<|reserved_special_token_129|>",
1077
+ "lstrip": false,
1078
+ "normalized": false,
1079
+ "rstrip": false,
1080
+ "single_word": false,
1081
+ "special": true
1082
+ },
1083
+ "128135": {
1084
+ "content": "<|reserved_special_token_130|>",
1085
+ "lstrip": false,
1086
+ "normalized": false,
1087
+ "rstrip": false,
1088
+ "single_word": false,
1089
+ "special": true
1090
+ },
1091
+ "128136": {
1092
+ "content": "<|reserved_special_token_131|>",
1093
+ "lstrip": false,
1094
+ "normalized": false,
1095
+ "rstrip": false,
1096
+ "single_word": false,
1097
+ "special": true
1098
+ },
1099
+ "128137": {
1100
+ "content": "<|reserved_special_token_132|>",
1101
+ "lstrip": false,
1102
+ "normalized": false,
1103
+ "rstrip": false,
1104
+ "single_word": false,
1105
+ "special": true
1106
+ },
1107
+ "128138": {
1108
+ "content": "<|reserved_special_token_133|>",
1109
+ "lstrip": false,
1110
+ "normalized": false,
1111
+ "rstrip": false,
1112
+ "single_word": false,
1113
+ "special": true
1114
+ },
1115
+ "128139": {
1116
+ "content": "<|reserved_special_token_134|>",
1117
+ "lstrip": false,
1118
+ "normalized": false,
1119
+ "rstrip": false,
1120
+ "single_word": false,
1121
+ "special": true
1122
+ },
1123
+ "128140": {
1124
+ "content": "<|reserved_special_token_135|>",
1125
+ "lstrip": false,
1126
+ "normalized": false,
1127
+ "rstrip": false,
1128
+ "single_word": false,
1129
+ "special": true
1130
+ },
1131
+ "128141": {
1132
+ "content": "<|reserved_special_token_136|>",
1133
+ "lstrip": false,
1134
+ "normalized": false,
1135
+ "rstrip": false,
1136
+ "single_word": false,
1137
+ "special": true
1138
+ },
1139
+ "128142": {
1140
+ "content": "<|reserved_special_token_137|>",
1141
+ "lstrip": false,
1142
+ "normalized": false,
1143
+ "rstrip": false,
1144
+ "single_word": false,
1145
+ "special": true
1146
+ },
1147
+ "128143": {
1148
+ "content": "<|reserved_special_token_138|>",
1149
+ "lstrip": false,
1150
+ "normalized": false,
1151
+ "rstrip": false,
1152
+ "single_word": false,
1153
+ "special": true
1154
+ },
1155
+ "128144": {
1156
+ "content": "<|reserved_special_token_139|>",
1157
+ "lstrip": false,
1158
+ "normalized": false,
1159
+ "rstrip": false,
1160
+ "single_word": false,
1161
+ "special": true
1162
+ },
1163
+ "128145": {
1164
+ "content": "<|reserved_special_token_140|>",
1165
+ "lstrip": false,
1166
+ "normalized": false,
1167
+ "rstrip": false,
1168
+ "single_word": false,
1169
+ "special": true
1170
+ },
1171
+ "128146": {
1172
+ "content": "<|reserved_special_token_141|>",
1173
+ "lstrip": false,
1174
+ "normalized": false,
1175
+ "rstrip": false,
1176
+ "single_word": false,
1177
+ "special": true
1178
+ },
1179
+ "128147": {
1180
+ "content": "<|reserved_special_token_142|>",
1181
+ "lstrip": false,
1182
+ "normalized": false,
1183
+ "rstrip": false,
1184
+ "single_word": false,
1185
+ "special": true
1186
+ },
1187
+ "128148": {
1188
+ "content": "<|reserved_special_token_143|>",
1189
+ "lstrip": false,
1190
+ "normalized": false,
1191
+ "rstrip": false,
1192
+ "single_word": false,
1193
+ "special": true
1194
+ },
1195
+ "128149": {
1196
+ "content": "<|reserved_special_token_144|>",
1197
+ "lstrip": false,
1198
+ "normalized": false,
1199
+ "rstrip": false,
1200
+ "single_word": false,
1201
+ "special": true
1202
+ },
1203
+ "128150": {
1204
+ "content": "<|reserved_special_token_145|>",
1205
+ "lstrip": false,
1206
+ "normalized": false,
1207
+ "rstrip": false,
1208
+ "single_word": false,
1209
+ "special": true
1210
+ },
1211
+ "128151": {
1212
+ "content": "<|reserved_special_token_146|>",
1213
+ "lstrip": false,
1214
+ "normalized": false,
1215
+ "rstrip": false,
1216
+ "single_word": false,
1217
+ "special": true
1218
+ },
1219
+ "128152": {
1220
+ "content": "<|reserved_special_token_147|>",
1221
+ "lstrip": false,
1222
+ "normalized": false,
1223
+ "rstrip": false,
1224
+ "single_word": false,
1225
+ "special": true
1226
+ },
1227
+ "128153": {
1228
+ "content": "<|reserved_special_token_148|>",
1229
+ "lstrip": false,
1230
+ "normalized": false,
1231
+ "rstrip": false,
1232
+ "single_word": false,
1233
+ "special": true
1234
+ },
1235
+ "128154": {
1236
+ "content": "<|reserved_special_token_149|>",
1237
+ "lstrip": false,
1238
+ "normalized": false,
1239
+ "rstrip": false,
1240
+ "single_word": false,
1241
+ "special": true
1242
+ },
1243
+ "128155": {
1244
+ "content": "<|reserved_special_token_150|>",
1245
+ "lstrip": false,
1246
+ "normalized": false,
1247
+ "rstrip": false,
1248
+ "single_word": false,
1249
+ "special": true
1250
+ },
1251
+ "128156": {
1252
+ "content": "<|reserved_special_token_151|>",
1253
+ "lstrip": false,
1254
+ "normalized": false,
1255
+ "rstrip": false,
1256
+ "single_word": false,
1257
+ "special": true
1258
+ },
1259
+ "128157": {
1260
+ "content": "<|reserved_special_token_152|>",
1261
+ "lstrip": false,
1262
+ "normalized": false,
1263
+ "rstrip": false,
1264
+ "single_word": false,
1265
+ "special": true
1266
+ },
1267
+ "128158": {
1268
+ "content": "<|reserved_special_token_153|>",
1269
+ "lstrip": false,
1270
+ "normalized": false,
1271
+ "rstrip": false,
1272
+ "single_word": false,
1273
+ "special": true
1274
+ },
1275
+ "128159": {
1276
+ "content": "<|reserved_special_token_154|>",
1277
+ "lstrip": false,
1278
+ "normalized": false,
1279
+ "rstrip": false,
1280
+ "single_word": false,
1281
+ "special": true
1282
+ },
1283
+ "128160": {
1284
+ "content": "<|reserved_special_token_155|>",
1285
+ "lstrip": false,
1286
+ "normalized": false,
1287
+ "rstrip": false,
1288
+ "single_word": false,
1289
+ "special": true
1290
+ },
1291
+ "128161": {
1292
+ "content": "<|reserved_special_token_156|>",
1293
+ "lstrip": false,
1294
+ "normalized": false,
1295
+ "rstrip": false,
1296
+ "single_word": false,
1297
+ "special": true
1298
+ },
1299
+ "128162": {
1300
+ "content": "<|reserved_special_token_157|>",
1301
+ "lstrip": false,
1302
+ "normalized": false,
1303
+ "rstrip": false,
1304
+ "single_word": false,
1305
+ "special": true
1306
+ },
1307
+ "128163": {
1308
+ "content": "<|reserved_special_token_158|>",
1309
+ "lstrip": false,
1310
+ "normalized": false,
1311
+ "rstrip": false,
1312
+ "single_word": false,
1313
+ "special": true
1314
+ },
1315
+ "128164": {
1316
+ "content": "<|reserved_special_token_159|>",
1317
+ "lstrip": false,
1318
+ "normalized": false,
1319
+ "rstrip": false,
1320
+ "single_word": false,
1321
+ "special": true
1322
+ },
1323
+ "128165": {
1324
+ "content": "<|reserved_special_token_160|>",
1325
+ "lstrip": false,
1326
+ "normalized": false,
1327
+ "rstrip": false,
1328
+ "single_word": false,
1329
+ "special": true
1330
+ },
1331
+ "128166": {
1332
+ "content": "<|reserved_special_token_161|>",
1333
+ "lstrip": false,
1334
+ "normalized": false,
1335
+ "rstrip": false,
1336
+ "single_word": false,
1337
+ "special": true
1338
+ },
1339
+ "128167": {
1340
+ "content": "<|reserved_special_token_162|>",
1341
+ "lstrip": false,
1342
+ "normalized": false,
1343
+ "rstrip": false,
1344
+ "single_word": false,
1345
+ "special": true
1346
+ },
1347
+ "128168": {
1348
+ "content": "<|reserved_special_token_163|>",
1349
+ "lstrip": false,
1350
+ "normalized": false,
1351
+ "rstrip": false,
1352
+ "single_word": false,
1353
+ "special": true
1354
+ },
1355
+ "128169": {
1356
+ "content": "<|reserved_special_token_164|>",
1357
+ "lstrip": false,
1358
+ "normalized": false,
1359
+ "rstrip": false,
1360
+ "single_word": false,
1361
+ "special": true
1362
+ },
1363
+ "128170": {
1364
+ "content": "<|reserved_special_token_165|>",
1365
+ "lstrip": false,
1366
+ "normalized": false,
1367
+ "rstrip": false,
1368
+ "single_word": false,
1369
+ "special": true
1370
+ },
1371
+ "128171": {
1372
+ "content": "<|reserved_special_token_166|>",
1373
+ "lstrip": false,
1374
+ "normalized": false,
1375
+ "rstrip": false,
1376
+ "single_word": false,
1377
+ "special": true
1378
+ },
1379
+ "128172": {
1380
+ "content": "<|reserved_special_token_167|>",
1381
+ "lstrip": false,
1382
+ "normalized": false,
1383
+ "rstrip": false,
1384
+ "single_word": false,
1385
+ "special": true
1386
+ },
1387
+ "128173": {
1388
+ "content": "<|reserved_special_token_168|>",
1389
+ "lstrip": false,
1390
+ "normalized": false,
1391
+ "rstrip": false,
1392
+ "single_word": false,
1393
+ "special": true
1394
+ },
1395
+ "128174": {
1396
+ "content": "<|reserved_special_token_169|>",
1397
+ "lstrip": false,
1398
+ "normalized": false,
1399
+ "rstrip": false,
1400
+ "single_word": false,
1401
+ "special": true
1402
+ },
1403
+ "128175": {
1404
+ "content": "<|reserved_special_token_170|>",
1405
+ "lstrip": false,
1406
+ "normalized": false,
1407
+ "rstrip": false,
1408
+ "single_word": false,
1409
+ "special": true
1410
+ },
1411
+ "128176": {
1412
+ "content": "<|reserved_special_token_171|>",
1413
+ "lstrip": false,
1414
+ "normalized": false,
1415
+ "rstrip": false,
1416
+ "single_word": false,
1417
+ "special": true
1418
+ },
1419
+ "128177": {
1420
+ "content": "<|reserved_special_token_172|>",
1421
+ "lstrip": false,
1422
+ "normalized": false,
1423
+ "rstrip": false,
1424
+ "single_word": false,
1425
+ "special": true
1426
+ },
1427
+ "128178": {
1428
+ "content": "<|reserved_special_token_173|>",
1429
+ "lstrip": false,
1430
+ "normalized": false,
1431
+ "rstrip": false,
1432
+ "single_word": false,
1433
+ "special": true
1434
+ },
1435
+ "128179": {
1436
+ "content": "<|reserved_special_token_174|>",
1437
+ "lstrip": false,
1438
+ "normalized": false,
1439
+ "rstrip": false,
1440
+ "single_word": false,
1441
+ "special": true
1442
+ },
1443
+ "128180": {
1444
+ "content": "<|reserved_special_token_175|>",
1445
+ "lstrip": false,
1446
+ "normalized": false,
1447
+ "rstrip": false,
1448
+ "single_word": false,
1449
+ "special": true
1450
+ },
1451
+ "128181": {
1452
+ "content": "<|reserved_special_token_176|>",
1453
+ "lstrip": false,
1454
+ "normalized": false,
1455
+ "rstrip": false,
1456
+ "single_word": false,
1457
+ "special": true
1458
+ },
1459
+ "128182": {
1460
+ "content": "<|reserved_special_token_177|>",
1461
+ "lstrip": false,
1462
+ "normalized": false,
1463
+ "rstrip": false,
1464
+ "single_word": false,
1465
+ "special": true
1466
+ },
1467
+ "128183": {
1468
+ "content": "<|reserved_special_token_178|>",
1469
+ "lstrip": false,
1470
+ "normalized": false,
1471
+ "rstrip": false,
1472
+ "single_word": false,
1473
+ "special": true
1474
+ },
1475
+ "128184": {
1476
+ "content": "<|reserved_special_token_179|>",
1477
+ "lstrip": false,
1478
+ "normalized": false,
1479
+ "rstrip": false,
1480
+ "single_word": false,
1481
+ "special": true
1482
+ },
1483
+ "128185": {
1484
+ "content": "<|reserved_special_token_180|>",
1485
+ "lstrip": false,
1486
+ "normalized": false,
1487
+ "rstrip": false,
1488
+ "single_word": false,
1489
+ "special": true
1490
+ },
1491
+ "128186": {
1492
+ "content": "<|reserved_special_token_181|>",
1493
+ "lstrip": false,
1494
+ "normalized": false,
1495
+ "rstrip": false,
1496
+ "single_word": false,
1497
+ "special": true
1498
+ },
1499
+ "128187": {
1500
+ "content": "<|reserved_special_token_182|>",
1501
+ "lstrip": false,
1502
+ "normalized": false,
1503
+ "rstrip": false,
1504
+ "single_word": false,
1505
+ "special": true
1506
+ },
1507
+ "128188": {
1508
+ "content": "<|reserved_special_token_183|>",
1509
+ "lstrip": false,
1510
+ "normalized": false,
1511
+ "rstrip": false,
1512
+ "single_word": false,
1513
+ "special": true
1514
+ },
1515
+ "128189": {
1516
+ "content": "<|reserved_special_token_184|>",
1517
+ "lstrip": false,
1518
+ "normalized": false,
1519
+ "rstrip": false,
1520
+ "single_word": false,
1521
+ "special": true
1522
+ },
1523
+ "128190": {
1524
+ "content": "<|reserved_special_token_185|>",
1525
+ "lstrip": false,
1526
+ "normalized": false,
1527
+ "rstrip": false,
1528
+ "single_word": false,
1529
+ "special": true
1530
+ },
1531
+ "128191": {
1532
+ "content": "<|reserved_special_token_186|>",
1533
+ "lstrip": false,
1534
+ "normalized": false,
1535
+ "rstrip": false,
1536
+ "single_word": false,
1537
+ "special": true
1538
+ },
1539
+ "128192": {
1540
+ "content": "<|reserved_special_token_187|>",
1541
+ "lstrip": false,
1542
+ "normalized": false,
1543
+ "rstrip": false,
1544
+ "single_word": false,
1545
+ "special": true
1546
+ },
1547
+ "128193": {
1548
+ "content": "<|reserved_special_token_188|>",
1549
+ "lstrip": false,
1550
+ "normalized": false,
1551
+ "rstrip": false,
1552
+ "single_word": false,
1553
+ "special": true
1554
+ },
1555
+ "128194": {
1556
+ "content": "<|reserved_special_token_189|>",
1557
+ "lstrip": false,
1558
+ "normalized": false,
1559
+ "rstrip": false,
1560
+ "single_word": false,
1561
+ "special": true
1562
+ },
1563
+ "128195": {
1564
+ "content": "<|reserved_special_token_190|>",
1565
+ "lstrip": false,
1566
+ "normalized": false,
1567
+ "rstrip": false,
1568
+ "single_word": false,
1569
+ "special": true
1570
+ },
1571
+ "128196": {
1572
+ "content": "<|reserved_special_token_191|>",
1573
+ "lstrip": false,
1574
+ "normalized": false,
1575
+ "rstrip": false,
1576
+ "single_word": false,
1577
+ "special": true
1578
+ },
1579
+ "128197": {
1580
+ "content": "<|reserved_special_token_192|>",
1581
+ "lstrip": false,
1582
+ "normalized": false,
1583
+ "rstrip": false,
1584
+ "single_word": false,
1585
+ "special": true
1586
+ },
1587
+ "128198": {
1588
+ "content": "<|reserved_special_token_193|>",
1589
+ "lstrip": false,
1590
+ "normalized": false,
1591
+ "rstrip": false,
1592
+ "single_word": false,
1593
+ "special": true
1594
+ },
1595
+ "128199": {
1596
+ "content": "<|reserved_special_token_194|>",
1597
+ "lstrip": false,
1598
+ "normalized": false,
1599
+ "rstrip": false,
1600
+ "single_word": false,
1601
+ "special": true
1602
+ },
1603
+ "128200": {
1604
+ "content": "<|reserved_special_token_195|>",
1605
+ "lstrip": false,
1606
+ "normalized": false,
1607
+ "rstrip": false,
1608
+ "single_word": false,
1609
+ "special": true
1610
+ },
1611
+ "128201": {
1612
+ "content": "<|reserved_special_token_196|>",
1613
+ "lstrip": false,
1614
+ "normalized": false,
1615
+ "rstrip": false,
1616
+ "single_word": false,
1617
+ "special": true
1618
+ },
1619
+ "128202": {
1620
+ "content": "<|reserved_special_token_197|>",
1621
+ "lstrip": false,
1622
+ "normalized": false,
1623
+ "rstrip": false,
1624
+ "single_word": false,
1625
+ "special": true
1626
+ },
1627
+ "128203": {
1628
+ "content": "<|reserved_special_token_198|>",
1629
+ "lstrip": false,
1630
+ "normalized": false,
1631
+ "rstrip": false,
1632
+ "single_word": false,
1633
+ "special": true
1634
+ },
1635
+ "128204": {
1636
+ "content": "<|reserved_special_token_199|>",
1637
+ "lstrip": false,
1638
+ "normalized": false,
1639
+ "rstrip": false,
1640
+ "single_word": false,
1641
+ "special": true
1642
+ },
1643
+ "128205": {
1644
+ "content": "<|reserved_special_token_200|>",
1645
+ "lstrip": false,
1646
+ "normalized": false,
1647
+ "rstrip": false,
1648
+ "single_word": false,
1649
+ "special": true
1650
+ },
1651
+ "128206": {
1652
+ "content": "<|reserved_special_token_201|>",
1653
+ "lstrip": false,
1654
+ "normalized": false,
1655
+ "rstrip": false,
1656
+ "single_word": false,
1657
+ "special": true
1658
+ },
1659
+ "128207": {
1660
+ "content": "<|reserved_special_token_202|>",
1661
+ "lstrip": false,
1662
+ "normalized": false,
1663
+ "rstrip": false,
1664
+ "single_word": false,
1665
+ "special": true
1666
+ },
1667
+ "128208": {
1668
+ "content": "<|reserved_special_token_203|>",
1669
+ "lstrip": false,
1670
+ "normalized": false,
1671
+ "rstrip": false,
1672
+ "single_word": false,
1673
+ "special": true
1674
+ },
1675
+ "128209": {
1676
+ "content": "<|reserved_special_token_204|>",
1677
+ "lstrip": false,
1678
+ "normalized": false,
1679
+ "rstrip": false,
1680
+ "single_word": false,
1681
+ "special": true
1682
+ },
1683
+ "128210": {
1684
+ "content": "<|reserved_special_token_205|>",
1685
+ "lstrip": false,
1686
+ "normalized": false,
1687
+ "rstrip": false,
1688
+ "single_word": false,
1689
+ "special": true
1690
+ },
1691
+ "128211": {
1692
+ "content": "<|reserved_special_token_206|>",
1693
+ "lstrip": false,
1694
+ "normalized": false,
1695
+ "rstrip": false,
1696
+ "single_word": false,
1697
+ "special": true
1698
+ },
1699
+ "128212": {
1700
+ "content": "<|reserved_special_token_207|>",
1701
+ "lstrip": false,
1702
+ "normalized": false,
1703
+ "rstrip": false,
1704
+ "single_word": false,
1705
+ "special": true
1706
+ },
1707
+ "128213": {
1708
+ "content": "<|reserved_special_token_208|>",
1709
+ "lstrip": false,
1710
+ "normalized": false,
1711
+ "rstrip": false,
1712
+ "single_word": false,
1713
+ "special": true
1714
+ },
1715
+ "128214": {
1716
+ "content": "<|reserved_special_token_209|>",
1717
+ "lstrip": false,
1718
+ "normalized": false,
1719
+ "rstrip": false,
1720
+ "single_word": false,
1721
+ "special": true
1722
+ },
1723
+ "128215": {
1724
+ "content": "<|reserved_special_token_210|>",
1725
+ "lstrip": false,
1726
+ "normalized": false,
1727
+ "rstrip": false,
1728
+ "single_word": false,
1729
+ "special": true
1730
+ },
1731
+ "128216": {
1732
+ "content": "<|reserved_special_token_211|>",
1733
+ "lstrip": false,
1734
+ "normalized": false,
1735
+ "rstrip": false,
1736
+ "single_word": false,
1737
+ "special": true
1738
+ },
1739
+ "128217": {
1740
+ "content": "<|reserved_special_token_212|>",
1741
+ "lstrip": false,
1742
+ "normalized": false,
1743
+ "rstrip": false,
1744
+ "single_word": false,
1745
+ "special": true
1746
+ },
1747
+ "128218": {
1748
+ "content": "<|reserved_special_token_213|>",
1749
+ "lstrip": false,
1750
+ "normalized": false,
1751
+ "rstrip": false,
1752
+ "single_word": false,
1753
+ "special": true
1754
+ },
1755
+ "128219": {
1756
+ "content": "<|reserved_special_token_214|>",
1757
+ "lstrip": false,
1758
+ "normalized": false,
1759
+ "rstrip": false,
1760
+ "single_word": false,
1761
+ "special": true
1762
+ },
1763
+ "128220": {
1764
+ "content": "<|reserved_special_token_215|>",
1765
+ "lstrip": false,
1766
+ "normalized": false,
1767
+ "rstrip": false,
1768
+ "single_word": false,
1769
+ "special": true
1770
+ },
1771
+ "128221": {
1772
+ "content": "<|reserved_special_token_216|>",
1773
+ "lstrip": false,
1774
+ "normalized": false,
1775
+ "rstrip": false,
1776
+ "single_word": false,
1777
+ "special": true
1778
+ },
1779
+ "128222": {
1780
+ "content": "<|reserved_special_token_217|>",
1781
+ "lstrip": false,
1782
+ "normalized": false,
1783
+ "rstrip": false,
1784
+ "single_word": false,
1785
+ "special": true
1786
+ },
1787
+ "128223": {
1788
+ "content": "<|reserved_special_token_218|>",
1789
+ "lstrip": false,
1790
+ "normalized": false,
1791
+ "rstrip": false,
1792
+ "single_word": false,
1793
+ "special": true
1794
+ },
1795
+ "128224": {
1796
+ "content": "<|reserved_special_token_219|>",
1797
+ "lstrip": false,
1798
+ "normalized": false,
1799
+ "rstrip": false,
1800
+ "single_word": false,
1801
+ "special": true
1802
+ },
1803
+ "128225": {
1804
+ "content": "<|reserved_special_token_220|>",
1805
+ "lstrip": false,
1806
+ "normalized": false,
1807
+ "rstrip": false,
1808
+ "single_word": false,
1809
+ "special": true
1810
+ },
1811
+ "128226": {
1812
+ "content": "<|reserved_special_token_221|>",
1813
+ "lstrip": false,
1814
+ "normalized": false,
1815
+ "rstrip": false,
1816
+ "single_word": false,
1817
+ "special": true
1818
+ },
1819
+ "128227": {
1820
+ "content": "<|reserved_special_token_222|>",
1821
+ "lstrip": false,
1822
+ "normalized": false,
1823
+ "rstrip": false,
1824
+ "single_word": false,
1825
+ "special": true
1826
+ },
1827
+ "128228": {
1828
+ "content": "<|reserved_special_token_223|>",
1829
+ "lstrip": false,
1830
+ "normalized": false,
1831
+ "rstrip": false,
1832
+ "single_word": false,
1833
+ "special": true
1834
+ },
1835
+ "128229": {
1836
+ "content": "<|reserved_special_token_224|>",
1837
+ "lstrip": false,
1838
+ "normalized": false,
1839
+ "rstrip": false,
1840
+ "single_word": false,
1841
+ "special": true
1842
+ },
1843
+ "128230": {
1844
+ "content": "<|reserved_special_token_225|>",
1845
+ "lstrip": false,
1846
+ "normalized": false,
1847
+ "rstrip": false,
1848
+ "single_word": false,
1849
+ "special": true
1850
+ },
1851
+ "128231": {
1852
+ "content": "<|reserved_special_token_226|>",
1853
+ "lstrip": false,
1854
+ "normalized": false,
1855
+ "rstrip": false,
1856
+ "single_word": false,
1857
+ "special": true
1858
+ },
1859
+ "128232": {
1860
+ "content": "<|reserved_special_token_227|>",
1861
+ "lstrip": false,
1862
+ "normalized": false,
1863
+ "rstrip": false,
1864
+ "single_word": false,
1865
+ "special": true
1866
+ },
1867
+ "128233": {
1868
+ "content": "<|reserved_special_token_228|>",
1869
+ "lstrip": false,
1870
+ "normalized": false,
1871
+ "rstrip": false,
1872
+ "single_word": false,
1873
+ "special": true
1874
+ },
1875
+ "128234": {
1876
+ "content": "<|reserved_special_token_229|>",
1877
+ "lstrip": false,
1878
+ "normalized": false,
1879
+ "rstrip": false,
1880
+ "single_word": false,
1881
+ "special": true
1882
+ },
1883
+ "128235": {
1884
+ "content": "<|reserved_special_token_230|>",
1885
+ "lstrip": false,
1886
+ "normalized": false,
1887
+ "rstrip": false,
1888
+ "single_word": false,
1889
+ "special": true
1890
+ },
1891
+ "128236": {
1892
+ "content": "<|reserved_special_token_231|>",
1893
+ "lstrip": false,
1894
+ "normalized": false,
1895
+ "rstrip": false,
1896
+ "single_word": false,
1897
+ "special": true
1898
+ },
1899
+ "128237": {
1900
+ "content": "<|reserved_special_token_232|>",
1901
+ "lstrip": false,
1902
+ "normalized": false,
1903
+ "rstrip": false,
1904
+ "single_word": false,
1905
+ "special": true
1906
+ },
1907
+ "128238": {
1908
+ "content": "<|reserved_special_token_233|>",
1909
+ "lstrip": false,
1910
+ "normalized": false,
1911
+ "rstrip": false,
1912
+ "single_word": false,
1913
+ "special": true
1914
+ },
1915
+ "128239": {
1916
+ "content": "<|reserved_special_token_234|>",
1917
+ "lstrip": false,
1918
+ "normalized": false,
1919
+ "rstrip": false,
1920
+ "single_word": false,
1921
+ "special": true
1922
+ },
1923
+ "128240": {
1924
+ "content": "<|reserved_special_token_235|>",
1925
+ "lstrip": false,
1926
+ "normalized": false,
1927
+ "rstrip": false,
1928
+ "single_word": false,
1929
+ "special": true
1930
+ },
1931
+ "128241": {
1932
+ "content": "<|reserved_special_token_236|>",
1933
+ "lstrip": false,
1934
+ "normalized": false,
1935
+ "rstrip": false,
1936
+ "single_word": false,
1937
+ "special": true
1938
+ },
1939
+ "128242": {
1940
+ "content": "<|reserved_special_token_237|>",
1941
+ "lstrip": false,
1942
+ "normalized": false,
1943
+ "rstrip": false,
1944
+ "single_word": false,
1945
+ "special": true
1946
+ },
1947
+ "128243": {
1948
+ "content": "<|reserved_special_token_238|>",
1949
+ "lstrip": false,
1950
+ "normalized": false,
1951
+ "rstrip": false,
1952
+ "single_word": false,
1953
+ "special": true
1954
+ },
1955
+ "128244": {
1956
+ "content": "<|reserved_special_token_239|>",
1957
+ "lstrip": false,
1958
+ "normalized": false,
1959
+ "rstrip": false,
1960
+ "single_word": false,
1961
+ "special": true
1962
+ },
1963
+ "128245": {
1964
+ "content": "<|reserved_special_token_240|>",
1965
+ "lstrip": false,
1966
+ "normalized": false,
1967
+ "rstrip": false,
1968
+ "single_word": false,
1969
+ "special": true
1970
+ },
1971
+ "128246": {
1972
+ "content": "<|reserved_special_token_241|>",
1973
+ "lstrip": false,
1974
+ "normalized": false,
1975
+ "rstrip": false,
1976
+ "single_word": false,
1977
+ "special": true
1978
+ },
1979
+ "128247": {
1980
+ "content": "<|reserved_special_token_242|>",
1981
+ "lstrip": false,
1982
+ "normalized": false,
1983
+ "rstrip": false,
1984
+ "single_word": false,
1985
+ "special": true
1986
+ },
1987
+ "128248": {
1988
+ "content": "<|reserved_special_token_243|>",
1989
+ "lstrip": false,
1990
+ "normalized": false,
1991
+ "rstrip": false,
1992
+ "single_word": false,
1993
+ "special": true
1994
+ },
1995
+ "128249": {
1996
+ "content": "<|reserved_special_token_244|>",
1997
+ "lstrip": false,
1998
+ "normalized": false,
1999
+ "rstrip": false,
2000
+ "single_word": false,
2001
+ "special": true
2002
+ },
2003
+ "128250": {
2004
+ "content": "<|reserved_special_token_245|>",
2005
+ "lstrip": false,
2006
+ "normalized": false,
2007
+ "rstrip": false,
2008
+ "single_word": false,
2009
+ "special": true
2010
+ },
2011
+ "128251": {
2012
+ "content": "<|reserved_special_token_246|>",
2013
+ "lstrip": false,
2014
+ "normalized": false,
2015
+ "rstrip": false,
2016
+ "single_word": false,
2017
+ "special": true
2018
+ },
2019
+ "128252": {
2020
+ "content": "<|reserved_special_token_247|>",
2021
+ "lstrip": false,
2022
+ "normalized": false,
2023
+ "rstrip": false,
2024
+ "single_word": false,
2025
+ "special": true
2026
+ },
2027
+ "128253": {
2028
+ "content": "<|reserved_special_token_248|>",
2029
+ "lstrip": false,
2030
+ "normalized": false,
2031
+ "rstrip": false,
2032
+ "single_word": false,
2033
+ "special": true
2034
+ },
2035
+ "128254": {
2036
+ "content": "<|reserved_special_token_249|>",
2037
+ "lstrip": false,
2038
+ "normalized": false,
2039
+ "rstrip": false,
2040
+ "single_word": false,
2041
+ "special": true
2042
+ },
2043
+ "128255": {
2044
+ "content": "<|reserved_special_token_250|>",
2045
+ "lstrip": false,
2046
+ "normalized": false,
2047
+ "rstrip": false,
2048
+ "single_word": false,
2049
+ "special": true
2050
+ }
2051
+ },
2052
+ "bos_token": "<|begin_of_text|>",
2053
+ "chat_template": "{% set system_message = '#Role\nname: CollectiveAI 助手\n\n#Init\nYou act as CollectiveAI 助手, 你的职责是回答用户的问题' %}{% if messages[0]['role'] == 'system' %}{% set system_message = messages[0]['content'] %}{% endif %}{% if system_message is defined %}{{ '<|begin_of_text|>' + '<|start_header_id|>system<|end_header_id|>\\n\\n' + system_message + '<|eot_id|>' }}{% endif %}{% set before = namespace(role='system') %}{% for message in messages %}{% set content = message['content'] %}{% if message['role'] == 'user' %}{{'<|start_header_id|>user<|end_header_id|>\\n\\n' + content + '<|eot_id|><|start_header_id|>assistant<|end_header_id|>\\n\\n' }}{% elif message['role'] == 'assistant' and before.role == 'user' %}{{ content + '<|eot_id|>' }}{% elif message['role'] == 'assistant' and before.role != 'user' %}{{'<|start_header_id|>assistant<|end_header_id|>\\n\\n' + content + '<|eot_id|>' }}{% endif %}{% set before.role = message['role'] %}{% endfor %}",
2054
+ "clean_up_tokenization_spaces": true,
2055
+ "eos_token": "<|eot_id|>",
2056
+ "model_input_names": [
2057
+ "input_ids",
2058
+ "attention_mask"
2059
+ ],
2060
+ "model_max_length": 1000000000000000019884624838656,
2061
+ "pad_token": "<|eot_id|>",
2062
+ "padding_side": "right",
2063
+ "split_special_tokens": false,
2064
+ "tokenizer_class": "PreTrainedTokenizerFast"
2065
+ }
trainer_state.json ADDED
@@ -0,0 +1,1971 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": null,
3
+ "best_model_checkpoint": null,
4
+ "epoch": 1.7543859649122808,
5
+ "eval_steps": 100,
6
+ "global_step": 2500,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.007017543859649123,
13
+ "grad_norm": 0.0,
14
+ "learning_rate": 1e-06,
15
+ "loss": 1.3034,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.014035087719298246,
20
+ "grad_norm": 11.65329647064209,
21
+ "learning_rate": 9.999987849060752e-07,
22
+ "loss": 1.3006,
23
+ "step": 20
24
+ },
25
+ {
26
+ "epoch": 0.021052631578947368,
27
+ "grad_norm": 8.014320373535156,
28
+ "learning_rate": 9.999632438442366e-07,
29
+ "loss": 1.233,
30
+ "step": 30
31
+ },
32
+ {
33
+ "epoch": 0.028070175438596492,
34
+ "grad_norm": 7.890571594238281,
35
+ "learning_rate": 9.998660418225644e-07,
36
+ "loss": 1.1962,
37
+ "step": 40
38
+ },
39
+ {
40
+ "epoch": 0.03508771929824561,
41
+ "grad_norm": 7.12827205657959,
42
+ "learning_rate": 9.997081019722536e-07,
43
+ "loss": 1.2213,
44
+ "step": 50
45
+ },
46
+ {
47
+ "epoch": 0.042105263157894736,
48
+ "grad_norm": 7.200845718383789,
49
+ "learning_rate": 9.99489443484293e-07,
50
+ "loss": 1.1679,
51
+ "step": 60
52
+ },
53
+ {
54
+ "epoch": 0.04912280701754386,
55
+ "grad_norm": 7.650635242462158,
56
+ "learning_rate": 9.992100929274846e-07,
57
+ "loss": 1.1699,
58
+ "step": 70
59
+ },
60
+ {
61
+ "epoch": 0.056140350877192984,
62
+ "grad_norm": 7.227153778076172,
63
+ "learning_rate": 9.988700842452145e-07,
64
+ "loss": 1.1207,
65
+ "step": 80
66
+ },
67
+ {
68
+ "epoch": 0.06315789473684211,
69
+ "grad_norm": 7.5115532875061035,
70
+ "learning_rate": 9.984694587513297e-07,
71
+ "loss": 1.1387,
72
+ "step": 90
73
+ },
74
+ {
75
+ "epoch": 0.07017543859649122,
76
+ "grad_norm": 7.4819512367248535,
77
+ "learning_rate": 9.980082651251174e-07,
78
+ "loss": 1.1544,
79
+ "step": 100
80
+ },
81
+ {
82
+ "epoch": 0.07017543859649122,
83
+ "eval_loss": 1.1328155994415283,
84
+ "eval_runtime": 27.6835,
85
+ "eval_samples_per_second": 173.388,
86
+ "eval_steps_per_second": 2.709,
87
+ "step": 100
88
+ },
89
+ {
90
+ "epoch": 0.07719298245614035,
91
+ "grad_norm": 7.3147759437561035,
92
+ "learning_rate": 9.9748655940539e-07,
93
+ "loss": 1.1726,
94
+ "step": 110
95
+ },
96
+ {
97
+ "epoch": 0.08421052631578947,
98
+ "grad_norm": 7.672832489013672,
99
+ "learning_rate": 9.969044049836765e-07,
100
+ "loss": 1.115,
101
+ "step": 120
102
+ },
103
+ {
104
+ "epoch": 0.0912280701754386,
105
+ "grad_norm": 7.895420551300049,
106
+ "learning_rate": 9.962618725965194e-07,
107
+ "loss": 1.1274,
108
+ "step": 130
109
+ },
110
+ {
111
+ "epoch": 0.09824561403508772,
112
+ "grad_norm": 7.362156867980957,
113
+ "learning_rate": 9.955590403168798e-07,
114
+ "loss": 1.1401,
115
+ "step": 140
116
+ },
117
+ {
118
+ "epoch": 0.10526315789473684,
119
+ "grad_norm": 7.586355209350586,
120
+ "learning_rate": 9.947959935446506e-07,
121
+ "loss": 1.1543,
122
+ "step": 150
123
+ },
124
+ {
125
+ "epoch": 0.11228070175438597,
126
+ "grad_norm": 7.309718132019043,
127
+ "learning_rate": 9.939728249962806e-07,
128
+ "loss": 1.115,
129
+ "step": 160
130
+ },
131
+ {
132
+ "epoch": 0.11929824561403508,
133
+ "grad_norm": 7.269148826599121,
134
+ "learning_rate": 9.930896346935075e-07,
135
+ "loss": 1.0933,
136
+ "step": 170
137
+ },
138
+ {
139
+ "epoch": 0.12631578947368421,
140
+ "grad_norm": 7.365452766418457,
141
+ "learning_rate": 9.921465299512052e-07,
142
+ "loss": 1.0965,
143
+ "step": 180
144
+ },
145
+ {
146
+ "epoch": 0.13333333333333333,
147
+ "grad_norm": 7.434603214263916,
148
+ "learning_rate": 9.911436253643443e-07,
149
+ "loss": 1.0972,
150
+ "step": 190
151
+ },
152
+ {
153
+ "epoch": 0.14035087719298245,
154
+ "grad_norm": 7.557833194732666,
155
+ "learning_rate": 9.900810427940668e-07,
156
+ "loss": 1.1182,
157
+ "step": 200
158
+ },
159
+ {
160
+ "epoch": 0.14035087719298245,
161
+ "eval_loss": 1.1001578569412231,
162
+ "eval_runtime": 27.6607,
163
+ "eval_samples_per_second": 173.531,
164
+ "eval_steps_per_second": 2.711,
165
+ "step": 200
166
+ },
167
+ {
168
+ "epoch": 0.14736842105263157,
169
+ "grad_norm": 7.197221279144287,
170
+ "learning_rate": 9.889589113528808e-07,
171
+ "loss": 1.0991,
172
+ "step": 210
173
+ },
174
+ {
175
+ "epoch": 0.1543859649122807,
176
+ "grad_norm": 7.870287895202637,
177
+ "learning_rate": 9.8777736738897e-07,
178
+ "loss": 1.1135,
179
+ "step": 220
180
+ },
181
+ {
182
+ "epoch": 0.16140350877192983,
183
+ "grad_norm": 7.257969379425049,
184
+ "learning_rate": 9.865365544696286e-07,
185
+ "loss": 1.1207,
186
+ "step": 230
187
+ },
188
+ {
189
+ "epoch": 0.16842105263157894,
190
+ "grad_norm": 7.788718223571777,
191
+ "learning_rate": 9.852366233638143e-07,
192
+ "loss": 1.1084,
193
+ "step": 240
194
+ },
195
+ {
196
+ "epoch": 0.17543859649122806,
197
+ "grad_norm": 7.723772048950195,
198
+ "learning_rate": 9.838777320238312e-07,
199
+ "loss": 1.0881,
200
+ "step": 250
201
+ },
202
+ {
203
+ "epoch": 0.1824561403508772,
204
+ "grad_norm": 6.814189434051514,
205
+ "learning_rate": 9.824600455661351e-07,
206
+ "loss": 1.1118,
207
+ "step": 260
208
+ },
209
+ {
210
+ "epoch": 0.18947368421052632,
211
+ "grad_norm": 7.434762477874756,
212
+ "learning_rate": 9.809837362512718e-07,
213
+ "loss": 1.0948,
214
+ "step": 270
215
+ },
216
+ {
217
+ "epoch": 0.19649122807017544,
218
+ "grad_norm": 7.205653190612793,
219
+ "learning_rate": 9.794489834629454e-07,
220
+ "loss": 1.0837,
221
+ "step": 280
222
+ },
223
+ {
224
+ "epoch": 0.20350877192982456,
225
+ "grad_norm": 7.118565559387207,
226
+ "learning_rate": 9.77855973686222e-07,
227
+ "loss": 1.092,
228
+ "step": 290
229
+ },
230
+ {
231
+ "epoch": 0.21052631578947367,
232
+ "grad_norm": 7.293910503387451,
233
+ "learning_rate": 9.762049004848705e-07,
234
+ "loss": 1.1015,
235
+ "step": 300
236
+ },
237
+ {
238
+ "epoch": 0.21052631578947367,
239
+ "eval_loss": 1.0845627784729004,
240
+ "eval_runtime": 27.672,
241
+ "eval_samples_per_second": 173.461,
242
+ "eval_steps_per_second": 2.71,
243
+ "step": 300
244
+ },
245
+ {
246
+ "epoch": 0.21754385964912282,
247
+ "grad_norm": 7.512034893035889,
248
+ "learning_rate": 9.744959644778421e-07,
249
+ "loss": 1.0836,
250
+ "step": 310
251
+ },
252
+ {
253
+ "epoch": 0.22456140350877193,
254
+ "grad_norm": 7.277877330780029,
255
+ "learning_rate": 9.727293733148942e-07,
256
+ "loss": 1.0717,
257
+ "step": 320
258
+ },
259
+ {
260
+ "epoch": 0.23157894736842105,
261
+ "grad_norm": 7.781631946563721,
262
+ "learning_rate": 9.709053416513591e-07,
263
+ "loss": 1.0391,
264
+ "step": 330
265
+ },
266
+ {
267
+ "epoch": 0.23859649122807017,
268
+ "grad_norm": 7.217984199523926,
269
+ "learning_rate": 9.690240911220617e-07,
270
+ "loss": 1.1131,
271
+ "step": 340
272
+ },
273
+ {
274
+ "epoch": 0.24561403508771928,
275
+ "grad_norm": 7.256911277770996,
276
+ "learning_rate": 9.67085850314389e-07,
277
+ "loss": 1.0628,
278
+ "step": 350
279
+ },
280
+ {
281
+ "epoch": 0.25263157894736843,
282
+ "grad_norm": 7.053469657897949,
283
+ "learning_rate": 9.650908547405143e-07,
284
+ "loss": 1.0583,
285
+ "step": 360
286
+ },
287
+ {
288
+ "epoch": 0.2596491228070175,
289
+ "grad_norm": 7.0806498527526855,
290
+ "learning_rate": 9.630393468087817e-07,
291
+ "loss": 1.0714,
292
+ "step": 370
293
+ },
294
+ {
295
+ "epoch": 0.26666666666666666,
296
+ "grad_norm": 7.368037223815918,
297
+ "learning_rate": 9.609315757942502e-07,
298
+ "loss": 1.0629,
299
+ "step": 380
300
+ },
301
+ {
302
+ "epoch": 0.2736842105263158,
303
+ "grad_norm": 7.083371639251709,
304
+ "learning_rate": 9.58767797808406e-07,
305
+ "loss": 1.0748,
306
+ "step": 390
307
+ },
308
+ {
309
+ "epoch": 0.2807017543859649,
310
+ "grad_norm": 7.305485248565674,
311
+ "learning_rate": 9.565482757680414e-07,
312
+ "loss": 1.0736,
313
+ "step": 400
314
+ },
315
+ {
316
+ "epoch": 0.2807017543859649,
317
+ "eval_loss": 1.072194218635559,
318
+ "eval_runtime": 27.6671,
319
+ "eval_samples_per_second": 173.491,
320
+ "eval_steps_per_second": 2.711,
321
+ "step": 400
322
+ },
323
+ {
324
+ "epoch": 0.28771929824561404,
325
+ "grad_norm": 7.741823196411133,
326
+ "learning_rate": 9.542732793633097e-07,
327
+ "loss": 1.0913,
328
+ "step": 410
329
+ },
330
+ {
331
+ "epoch": 0.29473684210526313,
332
+ "grad_norm": 6.781225204467773,
333
+ "learning_rate": 9.519430850249549e-07,
334
+ "loss": 1.0826,
335
+ "step": 420
336
+ },
337
+ {
338
+ "epoch": 0.3017543859649123,
339
+ "grad_norm": 6.993170738220215,
340
+ "learning_rate": 9.495579758907229e-07,
341
+ "loss": 1.0472,
342
+ "step": 430
343
+ },
344
+ {
345
+ "epoch": 0.3087719298245614,
346
+ "grad_norm": 6.528597831726074,
347
+ "learning_rate": 9.471182417709586e-07,
348
+ "loss": 1.0795,
349
+ "step": 440
350
+ },
351
+ {
352
+ "epoch": 0.3157894736842105,
353
+ "grad_norm": 7.972232341766357,
354
+ "learning_rate": 9.446241791133907e-07,
355
+ "loss": 1.0656,
356
+ "step": 450
357
+ },
358
+ {
359
+ "epoch": 0.32280701754385965,
360
+ "grad_norm": 6.81664514541626,
361
+ "learning_rate": 9.420760909671118e-07,
362
+ "loss": 1.0888,
363
+ "step": 460
364
+ },
365
+ {
366
+ "epoch": 0.3298245614035088,
367
+ "grad_norm": 6.822625160217285,
368
+ "learning_rate": 9.394742869457546e-07,
369
+ "loss": 1.0448,
370
+ "step": 470
371
+ },
372
+ {
373
+ "epoch": 0.3368421052631579,
374
+ "grad_norm": 7.689866065979004,
375
+ "learning_rate": 9.368190831898723e-07,
376
+ "loss": 1.0705,
377
+ "step": 480
378
+ },
379
+ {
380
+ "epoch": 0.34385964912280703,
381
+ "grad_norm": 6.757457256317139,
382
+ "learning_rate": 9.341108023285237e-07,
383
+ "loss": 1.0321,
384
+ "step": 490
385
+ },
386
+ {
387
+ "epoch": 0.3508771929824561,
388
+ "grad_norm": 9.012947082519531,
389
+ "learning_rate": 9.313497734400721e-07,
390
+ "loss": 1.0783,
391
+ "step": 500
392
+ },
393
+ {
394
+ "epoch": 0.3508771929824561,
395
+ "eval_loss": 1.060664415359497,
396
+ "eval_runtime": 27.6699,
397
+ "eval_samples_per_second": 173.474,
398
+ "eval_steps_per_second": 2.711,
399
+ "step": 500
400
+ },
401
+ {
402
+ "epoch": 0.35789473684210527,
403
+ "grad_norm": 6.598055362701416,
404
+ "learning_rate": 9.28536332012199e-07,
405
+ "loss": 1.0526,
406
+ "step": 510
407
+ },
408
+ {
409
+ "epoch": 0.3649122807017544,
410
+ "grad_norm": 6.9514360427856445,
411
+ "learning_rate": 9.2567081990114e-07,
412
+ "loss": 1.055,
413
+ "step": 520
414
+ },
415
+ {
416
+ "epoch": 0.3719298245614035,
417
+ "grad_norm": 7.644222259521484,
418
+ "learning_rate": 9.227535852901462e-07,
419
+ "loss": 1.0546,
420
+ "step": 530
421
+ },
422
+ {
423
+ "epoch": 0.37894736842105264,
424
+ "grad_norm": 6.849003314971924,
425
+ "learning_rate": 9.197849826471773e-07,
426
+ "loss": 1.0819,
427
+ "step": 540
428
+ },
429
+ {
430
+ "epoch": 0.38596491228070173,
431
+ "grad_norm": 7.057733535766602,
432
+ "learning_rate": 9.167653726818304e-07,
433
+ "loss": 1.0708,
434
+ "step": 550
435
+ },
436
+ {
437
+ "epoch": 0.3929824561403509,
438
+ "grad_norm": 6.9738287925720215,
439
+ "learning_rate": 9.136951223015112e-07,
440
+ "loss": 1.0751,
441
+ "step": 560
442
+ },
443
+ {
444
+ "epoch": 0.4,
445
+ "grad_norm": 7.2269511222839355,
446
+ "learning_rate": 9.10574604566852e-07,
447
+ "loss": 1.0437,
448
+ "step": 570
449
+ },
450
+ {
451
+ "epoch": 0.4070175438596491,
452
+ "grad_norm": 7.4513654708862305,
453
+ "learning_rate": 9.074041986463808e-07,
454
+ "loss": 1.0553,
455
+ "step": 580
456
+ },
457
+ {
458
+ "epoch": 0.41403508771929826,
459
+ "grad_norm": 7.455415725708008,
460
+ "learning_rate": 9.041842897704501e-07,
461
+ "loss": 1.0671,
462
+ "step": 590
463
+ },
464
+ {
465
+ "epoch": 0.42105263157894735,
466
+ "grad_norm": 7.012011528015137,
467
+ "learning_rate": 9.009152691844284e-07,
468
+ "loss": 1.0663,
469
+ "step": 600
470
+ },
471
+ {
472
+ "epoch": 0.42105263157894735,
473
+ "eval_loss": 1.051626205444336,
474
+ "eval_runtime": 27.657,
475
+ "eval_samples_per_second": 173.555,
476
+ "eval_steps_per_second": 2.712,
477
+ "step": 600
478
+ },
479
+ {
480
+ "epoch": 0.4280701754385965,
481
+ "grad_norm": 6.606391429901123,
482
+ "learning_rate": 8.975975341011595e-07,
483
+ "loss": 1.0385,
484
+ "step": 610
485
+ },
486
+ {
487
+ "epoch": 0.43508771929824563,
488
+ "grad_norm": 7.090952396392822,
489
+ "learning_rate": 8.942314876526991e-07,
490
+ "loss": 1.0438,
491
+ "step": 620
492
+ },
493
+ {
494
+ "epoch": 0.4421052631578947,
495
+ "grad_norm": 7.45530891418457,
496
+ "learning_rate": 8.908175388413303e-07,
497
+ "loss": 1.0519,
498
+ "step": 630
499
+ },
500
+ {
501
+ "epoch": 0.44912280701754387,
502
+ "grad_norm": 7.6413960456848145,
503
+ "learning_rate": 8.873561024898667e-07,
504
+ "loss": 1.0705,
505
+ "step": 640
506
+ },
507
+ {
508
+ "epoch": 0.45614035087719296,
509
+ "grad_norm": 7.025049209594727,
510
+ "learning_rate": 8.838475991912481e-07,
511
+ "loss": 1.0548,
512
+ "step": 650
513
+ },
514
+ {
515
+ "epoch": 0.4631578947368421,
516
+ "grad_norm": 7.06046724319458,
517
+ "learning_rate": 8.802924552574345e-07,
518
+ "loss": 1.0465,
519
+ "step": 660
520
+ },
521
+ {
522
+ "epoch": 0.47017543859649125,
523
+ "grad_norm": 7.351295471191406,
524
+ "learning_rate": 8.766911026676063e-07,
525
+ "loss": 1.0575,
526
+ "step": 670
527
+ },
528
+ {
529
+ "epoch": 0.47719298245614034,
530
+ "grad_norm": 7.417140960693359,
531
+ "learning_rate": 8.730439790156751e-07,
532
+ "loss": 1.0686,
533
+ "step": 680
534
+ },
535
+ {
536
+ "epoch": 0.4842105263157895,
537
+ "grad_norm": 7.903563499450684,
538
+ "learning_rate": 8.693515274571121e-07,
539
+ "loss": 1.0776,
540
+ "step": 690
541
+ },
542
+ {
543
+ "epoch": 0.49122807017543857,
544
+ "grad_norm": 8.01221752166748,
545
+ "learning_rate": 8.656141966551018e-07,
546
+ "loss": 1.0621,
547
+ "step": 700
548
+ },
549
+ {
550
+ "epoch": 0.49122807017543857,
551
+ "eval_loss": 1.043724775314331,
552
+ "eval_runtime": 27.6712,
553
+ "eval_samples_per_second": 173.466,
554
+ "eval_steps_per_second": 2.71,
555
+ "step": 700
556
+ },
557
+ {
558
+ "epoch": 0.4982456140350877,
559
+ "grad_norm": 7.052249431610107,
560
+ "learning_rate": 8.618324407260249e-07,
561
+ "loss": 1.0738,
562
+ "step": 710
563
+ },
564
+ {
565
+ "epoch": 0.5052631578947369,
566
+ "grad_norm": 7.37591028213501,
567
+ "learning_rate": 8.5800671918428e-07,
568
+ "loss": 1.0607,
569
+ "step": 720
570
+ },
571
+ {
572
+ "epoch": 0.512280701754386,
573
+ "grad_norm": 7.373082160949707,
574
+ "learning_rate": 8.541374968864485e-07,
575
+ "loss": 1.0602,
576
+ "step": 730
577
+ },
578
+ {
579
+ "epoch": 0.519298245614035,
580
+ "grad_norm": 7.446669101715088,
581
+ "learning_rate": 8.502252439748112e-07,
582
+ "loss": 1.0462,
583
+ "step": 740
584
+ },
585
+ {
586
+ "epoch": 0.5263157894736842,
587
+ "grad_norm": 6.634714603424072,
588
+ "learning_rate": 8.462704358202216e-07,
589
+ "loss": 1.0308,
590
+ "step": 750
591
+ },
592
+ {
593
+ "epoch": 0.5333333333333333,
594
+ "grad_norm": 6.623584270477295,
595
+ "learning_rate": 8.422735529643443e-07,
596
+ "loss": 1.0462,
597
+ "step": 760
598
+ },
599
+ {
600
+ "epoch": 0.5403508771929825,
601
+ "grad_norm": 7.110071659088135,
602
+ "learning_rate": 8.382350810612663e-07,
603
+ "loss": 1.0739,
604
+ "step": 770
605
+ },
606
+ {
607
+ "epoch": 0.5473684210526316,
608
+ "grad_norm": 7.406259536743164,
609
+ "learning_rate": 8.341555108184849e-07,
610
+ "loss": 1.069,
611
+ "step": 780
612
+ },
613
+ {
614
+ "epoch": 0.5543859649122806,
615
+ "grad_norm": 7.356163024902344,
616
+ "learning_rate": 8.300353379372833e-07,
617
+ "loss": 1.0542,
618
+ "step": 790
619
+ },
620
+ {
621
+ "epoch": 0.5614035087719298,
622
+ "grad_norm": 7.522149562835693,
623
+ "learning_rate": 8.258750630524983e-07,
624
+ "loss": 1.0482,
625
+ "step": 800
626
+ },
627
+ {
628
+ "epoch": 0.5614035087719298,
629
+ "eval_loss": 1.0357595682144165,
630
+ "eval_runtime": 27.6785,
631
+ "eval_samples_per_second": 173.42,
632
+ "eval_steps_per_second": 2.71,
633
+ "step": 800
634
+ },
635
+ {
636
+ "epoch": 0.5684210526315789,
637
+ "grad_norm": 6.716446399688721,
638
+ "learning_rate": 8.216751916716899e-07,
639
+ "loss": 1.0459,
640
+ "step": 810
641
+ },
642
+ {
643
+ "epoch": 0.5754385964912281,
644
+ "grad_norm": 7.719761371612549,
645
+ "learning_rate": 8.174362341137176e-07,
646
+ "loss": 1.0271,
647
+ "step": 820
648
+ },
649
+ {
650
+ "epoch": 0.5824561403508772,
651
+ "grad_norm": 7.073091983795166,
652
+ "learning_rate": 8.13158705446732e-07,
653
+ "loss": 1.0483,
654
+ "step": 830
655
+ },
656
+ {
657
+ "epoch": 0.5894736842105263,
658
+ "grad_norm": 6.979051113128662,
659
+ "learning_rate": 8.088431254255898e-07,
660
+ "loss": 1.0293,
661
+ "step": 840
662
+ },
663
+ {
664
+ "epoch": 0.5964912280701754,
665
+ "grad_norm": 7.095376014709473,
666
+ "learning_rate": 8.044900184287006e-07,
667
+ "loss": 1.0387,
668
+ "step": 850
669
+ },
670
+ {
671
+ "epoch": 0.6035087719298246,
672
+ "grad_norm": 7.155153274536133,
673
+ "learning_rate": 8.000999133943092e-07,
674
+ "loss": 1.0448,
675
+ "step": 860
676
+ },
677
+ {
678
+ "epoch": 0.6105263157894737,
679
+ "grad_norm": 7.818843841552734,
680
+ "learning_rate": 7.956733437562258e-07,
681
+ "loss": 1.047,
682
+ "step": 870
683
+ },
684
+ {
685
+ "epoch": 0.6175438596491228,
686
+ "grad_norm": 7.174437046051025,
687
+ "learning_rate": 7.912108473790091e-07,
688
+ "loss": 1.0293,
689
+ "step": 880
690
+ },
691
+ {
692
+ "epoch": 0.624561403508772,
693
+ "grad_norm": 7.124237060546875,
694
+ "learning_rate": 7.867129664926123e-07,
695
+ "loss": 1.0535,
696
+ "step": 890
697
+ },
698
+ {
699
+ "epoch": 0.631578947368421,
700
+ "grad_norm": 7.362142562866211,
701
+ "learning_rate": 7.821802476264965e-07,
702
+ "loss": 1.0662,
703
+ "step": 900
704
+ },
705
+ {
706
+ "epoch": 0.631578947368421,
707
+ "eval_loss": 1.0292896032333374,
708
+ "eval_runtime": 27.6513,
709
+ "eval_samples_per_second": 173.59,
710
+ "eval_steps_per_second": 2.712,
711
+ "step": 900
712
+ },
713
+ {
714
+ "epoch": 0.6385964912280702,
715
+ "grad_norm": 6.185942649841309,
716
+ "learning_rate": 7.776132415432232e-07,
717
+ "loss": 1.0311,
718
+ "step": 910
719
+ },
720
+ {
721
+ "epoch": 0.6456140350877193,
722
+ "grad_norm": 7.229496955871582,
723
+ "learning_rate": 7.73012503171533e-07,
724
+ "loss": 1.0478,
725
+ "step": 920
726
+ },
727
+ {
728
+ "epoch": 0.6526315789473685,
729
+ "grad_norm": 6.964082717895508,
730
+ "learning_rate": 7.683785915389162e-07,
731
+ "loss": 1.0355,
732
+ "step": 930
733
+ },
734
+ {
735
+ "epoch": 0.6596491228070176,
736
+ "grad_norm": 7.6486077308654785,
737
+ "learning_rate": 7.637120697036865e-07,
738
+ "loss": 1.0078,
739
+ "step": 940
740
+ },
741
+ {
742
+ "epoch": 0.6666666666666666,
743
+ "grad_norm": 7.581448554992676,
744
+ "learning_rate": 7.590135046865651e-07,
745
+ "loss": 1.0352,
746
+ "step": 950
747
+ },
748
+ {
749
+ "epoch": 0.6736842105263158,
750
+ "grad_norm": 6.977712154388428,
751
+ "learning_rate": 7.542834674017831e-07,
752
+ "loss": 1.0352,
753
+ "step": 960
754
+ },
755
+ {
756
+ "epoch": 0.6807017543859649,
757
+ "grad_norm": 7.210628986358643,
758
+ "learning_rate": 7.495225325877103e-07,
759
+ "loss": 1.0351,
760
+ "step": 970
761
+ },
762
+ {
763
+ "epoch": 0.6877192982456141,
764
+ "grad_norm": 6.860006809234619,
765
+ "learning_rate": 7.447312787370202e-07,
766
+ "loss": 1.0244,
767
+ "step": 980
768
+ },
769
+ {
770
+ "epoch": 0.6947368421052632,
771
+ "grad_norm": 7.080367088317871,
772
+ "learning_rate": 7.399102880263983e-07,
773
+ "loss": 1.0451,
774
+ "step": 990
775
+ },
776
+ {
777
+ "epoch": 0.7017543859649122,
778
+ "grad_norm": 7.036980152130127,
779
+ "learning_rate": 7.350601462458024e-07,
780
+ "loss": 1.0727,
781
+ "step": 1000
782
+ },
783
+ {
784
+ "epoch": 0.7017543859649122,
785
+ "eval_loss": 1.022666096687317,
786
+ "eval_runtime": 27.6533,
787
+ "eval_samples_per_second": 173.578,
788
+ "eval_steps_per_second": 2.712,
789
+ "step": 1000
790
+ },
791
+ {
792
+ "epoch": 0.7087719298245614,
793
+ "grad_norm": 6.67840576171875,
794
+ "learning_rate": 7.301814427272848e-07,
795
+ "loss": 1.0636,
796
+ "step": 1010
797
+ },
798
+ {
799
+ "epoch": 0.7157894736842105,
800
+ "grad_norm": 7.1095452308654785,
801
+ "learning_rate": 7.252747702733839e-07,
802
+ "loss": 1.0088,
803
+ "step": 1020
804
+ },
805
+ {
806
+ "epoch": 0.7228070175438597,
807
+ "grad_norm": 7.100186347961426,
808
+ "learning_rate": 7.203407250850928e-07,
809
+ "loss": 1.0245,
810
+ "step": 1030
811
+ },
812
+ {
813
+ "epoch": 0.7298245614035088,
814
+ "grad_norm": 6.765640735626221,
815
+ "learning_rate": 7.158771761692464e-07,
816
+ "loss": 1.0095,
817
+ "step": 1040
818
+ },
819
+ {
820
+ "epoch": 0.7368421052631579,
821
+ "grad_norm": 6.90313720703125,
822
+ "learning_rate": 7.108927771727661e-07,
823
+ "loss": 1.0188,
824
+ "step": 1050
825
+ },
826
+ {
827
+ "epoch": 0.743859649122807,
828
+ "grad_norm": 6.8065948486328125,
829
+ "learning_rate": 7.058827529721525e-07,
830
+ "loss": 1.0339,
831
+ "step": 1060
832
+ },
833
+ {
834
+ "epoch": 0.7508771929824561,
835
+ "grad_norm": 6.624533653259277,
836
+ "learning_rate": 7.008477123264847e-07,
837
+ "loss": 1.0346,
838
+ "step": 1070
839
+ },
840
+ {
841
+ "epoch": 0.7578947368421053,
842
+ "grad_norm": 7.218606472015381,
843
+ "learning_rate": 6.957882670345458e-07,
844
+ "loss": 1.0379,
845
+ "step": 1080
846
+ },
847
+ {
848
+ "epoch": 0.7649122807017544,
849
+ "grad_norm": 7.127339839935303,
850
+ "learning_rate": 6.90705031860483e-07,
851
+ "loss": 1.0205,
852
+ "step": 1090
853
+ },
854
+ {
855
+ "epoch": 0.7719298245614035,
856
+ "grad_norm": 6.587140083312988,
857
+ "learning_rate": 6.855986244591103e-07,
858
+ "loss": 1.0263,
859
+ "step": 1100
860
+ },
861
+ {
862
+ "epoch": 0.7719298245614035,
863
+ "eval_loss": 1.0174767971038818,
864
+ "eval_runtime": 27.6964,
865
+ "eval_samples_per_second": 173.308,
866
+ "eval_steps_per_second": 2.708,
867
+ "step": 1100
868
+ },
869
+ {
870
+ "epoch": 0.7789473684210526,
871
+ "grad_norm": 6.751448631286621,
872
+ "learning_rate": 6.804696653008574e-07,
873
+ "loss": 0.981,
874
+ "step": 1110
875
+ },
876
+ {
877
+ "epoch": 0.7859649122807018,
878
+ "grad_norm": 7.036713600158691,
879
+ "learning_rate": 6.753187775963772e-07,
880
+ "loss": 1.0488,
881
+ "step": 1120
882
+ },
883
+ {
884
+ "epoch": 0.7929824561403509,
885
+ "grad_norm": 6.959472179412842,
886
+ "learning_rate": 6.701465872208216e-07,
887
+ "loss": 1.0202,
888
+ "step": 1130
889
+ },
890
+ {
891
+ "epoch": 0.8,
892
+ "grad_norm": 7.4908599853515625,
893
+ "learning_rate": 6.649537226377914e-07,
894
+ "loss": 1.0356,
895
+ "step": 1140
896
+ },
897
+ {
898
+ "epoch": 0.8070175438596491,
899
+ "grad_norm": 8.565585136413574,
900
+ "learning_rate": 6.597408148229741e-07,
901
+ "loss": 1.0125,
902
+ "step": 1150
903
+ },
904
+ {
905
+ "epoch": 0.8140350877192982,
906
+ "grad_norm": 7.0569167137146,
907
+ "learning_rate": 6.545084971874736e-07,
908
+ "loss": 1.0654,
909
+ "step": 1160
910
+ },
911
+ {
912
+ "epoch": 0.8210526315789474,
913
+ "grad_norm": 6.795130252838135,
914
+ "learning_rate": 6.492574055008473e-07,
915
+ "loss": 1.046,
916
+ "step": 1170
917
+ },
918
+ {
919
+ "epoch": 0.8280701754385965,
920
+ "grad_norm": 7.272831916809082,
921
+ "learning_rate": 6.439881778138531e-07,
922
+ "loss": 1.0238,
923
+ "step": 1180
924
+ },
925
+ {
926
+ "epoch": 0.8350877192982457,
927
+ "grad_norm": 6.588538646697998,
928
+ "learning_rate": 6.387014543809223e-07,
929
+ "loss": 1.0155,
930
+ "step": 1190
931
+ },
932
+ {
933
+ "epoch": 0.8421052631578947,
934
+ "grad_norm": 6.798887252807617,
935
+ "learning_rate": 6.333978775823631e-07,
936
+ "loss": 1.0187,
937
+ "step": 1200
938
+ },
939
+ {
940
+ "epoch": 0.8421052631578947,
941
+ "eval_loss": 1.0141297578811646,
942
+ "eval_runtime": 27.6602,
943
+ "eval_samples_per_second": 173.534,
944
+ "eval_steps_per_second": 2.711,
945
+ "step": 1200
946
+ },
947
+ {
948
+ "epoch": 0.8491228070175438,
949
+ "grad_norm": 6.572112083435059,
950
+ "learning_rate": 6.280780918463057e-07,
951
+ "loss": 1.0355,
952
+ "step": 1210
953
+ },
954
+ {
955
+ "epoch": 0.856140350877193,
956
+ "grad_norm": 7.28840970993042,
957
+ "learning_rate": 6.227427435703995e-07,
958
+ "loss": 1.0424,
959
+ "step": 1220
960
+ },
961
+ {
962
+ "epoch": 0.8631578947368421,
963
+ "grad_norm": 8.068036079406738,
964
+ "learning_rate": 6.173924810432704e-07,
965
+ "loss": 1.0321,
966
+ "step": 1230
967
+ },
968
+ {
969
+ "epoch": 0.8701754385964913,
970
+ "grad_norm": 6.726752281188965,
971
+ "learning_rate": 6.12027954365748e-07,
972
+ "loss": 1.0431,
973
+ "step": 1240
974
+ },
975
+ {
976
+ "epoch": 0.8771929824561403,
977
+ "grad_norm": 6.742453098297119,
978
+ "learning_rate": 6.066498153718734e-07,
979
+ "loss": 1.0178,
980
+ "step": 1250
981
+ },
982
+ {
983
+ "epoch": 0.8842105263157894,
984
+ "grad_norm": 6.598849296569824,
985
+ "learning_rate": 6.01258717549696e-07,
986
+ "loss": 1.0141,
987
+ "step": 1260
988
+ },
989
+ {
990
+ "epoch": 0.8912280701754386,
991
+ "grad_norm": 6.771568775177002,
992
+ "learning_rate": 5.958553159618692e-07,
993
+ "loss": 0.9957,
994
+ "step": 1270
995
+ },
996
+ {
997
+ "epoch": 0.8982456140350877,
998
+ "grad_norm": 7.0470380783081055,
999
+ "learning_rate": 5.90440267166055e-07,
1000
+ "loss": 1.0387,
1001
+ "step": 1280
1002
+ },
1003
+ {
1004
+ "epoch": 0.9052631578947369,
1005
+ "grad_norm": 7.024428367614746,
1006
+ "learning_rate": 5.850142291351465e-07,
1007
+ "loss": 1.026,
1008
+ "step": 1290
1009
+ },
1010
+ {
1011
+ "epoch": 0.9122807017543859,
1012
+ "grad_norm": 7.074985027313232,
1013
+ "learning_rate": 5.795778611773197e-07,
1014
+ "loss": 1.0121,
1015
+ "step": 1300
1016
+ },
1017
+ {
1018
+ "epoch": 0.9122807017543859,
1019
+ "eval_loss": 1.0093048810958862,
1020
+ "eval_runtime": 27.6576,
1021
+ "eval_samples_per_second": 173.551,
1022
+ "eval_steps_per_second": 2.712,
1023
+ "step": 1300
1024
+ },
1025
+ {
1026
+ "epoch": 0.9192982456140351,
1027
+ "grad_norm": 7.012327194213867,
1028
+ "learning_rate": 5.741318238559209e-07,
1029
+ "loss": 1.0331,
1030
+ "step": 1310
1031
+ },
1032
+ {
1033
+ "epoch": 0.9263157894736842,
1034
+ "grad_norm": 6.710480690002441,
1035
+ "learning_rate": 5.686767789092041e-07,
1036
+ "loss": 1.012,
1037
+ "step": 1320
1038
+ },
1039
+ {
1040
+ "epoch": 0.9333333333333333,
1041
+ "grad_norm": 6.7387919425964355,
1042
+ "learning_rate": 5.632133891699231e-07,
1043
+ "loss": 0.9881,
1044
+ "step": 1330
1045
+ },
1046
+ {
1047
+ "epoch": 0.9403508771929825,
1048
+ "grad_norm": 6.965381145477295,
1049
+ "learning_rate": 5.577423184847931e-07,
1050
+ "loss": 1.0209,
1051
+ "step": 1340
1052
+ },
1053
+ {
1054
+ "epoch": 0.9473684210526315,
1055
+ "grad_norm": 7.125399589538574,
1056
+ "learning_rate": 5.522642316338268e-07,
1057
+ "loss": 1.0109,
1058
+ "step": 1350
1059
+ },
1060
+ {
1061
+ "epoch": 0.9543859649122807,
1062
+ "grad_norm": 7.273198127746582,
1063
+ "learning_rate": 5.467797942495589e-07,
1064
+ "loss": 1.0108,
1065
+ "step": 1360
1066
+ },
1067
+ {
1068
+ "epoch": 0.9614035087719298,
1069
+ "grad_norm": 6.802534580230713,
1070
+ "learning_rate": 5.412896727361662e-07,
1071
+ "loss": 1.025,
1072
+ "step": 1370
1073
+ },
1074
+ {
1075
+ "epoch": 0.968421052631579,
1076
+ "grad_norm": 7.282257080078125,
1077
+ "learning_rate": 5.357945341884935e-07,
1078
+ "loss": 1.0353,
1079
+ "step": 1380
1080
+ },
1081
+ {
1082
+ "epoch": 0.9754385964912281,
1083
+ "grad_norm": 6.752053260803223,
1084
+ "learning_rate": 5.302950463109969e-07,
1085
+ "loss": 1.0118,
1086
+ "step": 1390
1087
+ },
1088
+ {
1089
+ "epoch": 0.9824561403508771,
1090
+ "grad_norm": 6.847274303436279,
1091
+ "learning_rate": 5.247918773366111e-07,
1092
+ "loss": 1.0092,
1093
+ "step": 1400
1094
+ },
1095
+ {
1096
+ "epoch": 0.9824561403508771,
1097
+ "eval_loss": 1.003943681716919,
1098
+ "eval_runtime": 27.6644,
1099
+ "eval_samples_per_second": 173.508,
1100
+ "eval_steps_per_second": 2.711,
1101
+ "step": 1400
1102
+ },
1103
+ {
1104
+ "epoch": 0.9894736842105263,
1105
+ "grad_norm": 7.226211071014404,
1106
+ "learning_rate": 5.192856959455552e-07,
1107
+ "loss": 1.0278,
1108
+ "step": 1410
1109
+ },
1110
+ {
1111
+ "epoch": 0.9964912280701754,
1112
+ "grad_norm": 6.635247230529785,
1113
+ "learning_rate": 5.137771711840811e-07,
1114
+ "loss": 1.0163,
1115
+ "step": 1420
1116
+ },
1117
+ {
1118
+ "epoch": 1.0035087719298246,
1119
+ "grad_norm": 6.2100605964660645,
1120
+ "learning_rate": 5.082669723831793e-07,
1121
+ "loss": 0.928,
1122
+ "step": 1430
1123
+ },
1124
+ {
1125
+ "epoch": 1.0105263157894737,
1126
+ "grad_norm": 6.735259532928467,
1127
+ "learning_rate": 5.027557690772503e-07,
1128
+ "loss": 0.8903,
1129
+ "step": 1440
1130
+ },
1131
+ {
1132
+ "epoch": 1.0175438596491229,
1133
+ "grad_norm": 7.061236381530762,
1134
+ "learning_rate": 4.972442309227498e-07,
1135
+ "loss": 0.8721,
1136
+ "step": 1450
1137
+ },
1138
+ {
1139
+ "epoch": 1.024561403508772,
1140
+ "grad_norm": 6.729221820831299,
1141
+ "learning_rate": 4.917330276168208e-07,
1142
+ "loss": 0.8759,
1143
+ "step": 1460
1144
+ },
1145
+ {
1146
+ "epoch": 1.0315789473684212,
1147
+ "grad_norm": 6.925577640533447,
1148
+ "learning_rate": 4.86222828815919e-07,
1149
+ "loss": 0.866,
1150
+ "step": 1470
1151
+ },
1152
+ {
1153
+ "epoch": 1.03859649122807,
1154
+ "grad_norm": 6.847450256347656,
1155
+ "learning_rate": 4.807143040544446e-07,
1156
+ "loss": 0.8851,
1157
+ "step": 1480
1158
+ },
1159
+ {
1160
+ "epoch": 1.0456140350877192,
1161
+ "grad_norm": 7.24519157409668,
1162
+ "learning_rate": 4.752081226633888e-07,
1163
+ "loss": 0.8922,
1164
+ "step": 1490
1165
+ },
1166
+ {
1167
+ "epoch": 1.0526315789473684,
1168
+ "grad_norm": 6.8135085105896,
1169
+ "learning_rate": 4.697049536890033e-07,
1170
+ "loss": 0.8917,
1171
+ "step": 1500
1172
+ },
1173
+ {
1174
+ "epoch": 1.0526315789473684,
1175
+ "eval_loss": 1.0086382627487183,
1176
+ "eval_runtime": 27.6965,
1177
+ "eval_samples_per_second": 173.307,
1178
+ "eval_steps_per_second": 2.708,
1179
+ "step": 1500
1180
+ },
1181
+ {
1182
+ "epoch": 1.0596491228070175,
1183
+ "grad_norm": 6.774071216583252,
1184
+ "learning_rate": 4.6475522990138276e-07,
1185
+ "loss": 0.8773,
1186
+ "step": 1510
1187
+ },
1188
+ {
1189
+ "epoch": 1.0666666666666667,
1190
+ "grad_norm": 6.860315799713135,
1191
+ "learning_rate": 4.592596263646712e-07,
1192
+ "loss": 0.9042,
1193
+ "step": 1520
1194
+ },
1195
+ {
1196
+ "epoch": 1.0736842105263158,
1197
+ "grad_norm": 7.362914085388184,
1198
+ "learning_rate": 4.5376897311788825e-07,
1199
+ "loss": 0.8973,
1200
+ "step": 1530
1201
+ },
1202
+ {
1203
+ "epoch": 1.080701754385965,
1204
+ "grad_norm": 6.993128776550293,
1205
+ "learning_rate": 4.48283937320489e-07,
1206
+ "loss": 0.8533,
1207
+ "step": 1540
1208
+ },
1209
+ {
1210
+ "epoch": 1.087719298245614,
1211
+ "grad_norm": 7.575523853302002,
1212
+ "learning_rate": 4.4280518544936224e-07,
1213
+ "loss": 0.8896,
1214
+ "step": 1550
1215
+ },
1216
+ {
1217
+ "epoch": 1.0947368421052632,
1218
+ "grad_norm": 7.457510948181152,
1219
+ "learning_rate": 4.3733338321784777e-07,
1220
+ "loss": 0.873,
1221
+ "step": 1560
1222
+ },
1223
+ {
1224
+ "epoch": 1.1017543859649124,
1225
+ "grad_norm": 6.553786754608154,
1226
+ "learning_rate": 4.3186919549484777e-07,
1227
+ "loss": 0.8735,
1228
+ "step": 1570
1229
+ },
1230
+ {
1231
+ "epoch": 1.1087719298245613,
1232
+ "grad_norm": 7.161813259124756,
1233
+ "learning_rate": 4.264132862240387e-07,
1234
+ "loss": 0.8708,
1235
+ "step": 1580
1236
+ },
1237
+ {
1238
+ "epoch": 1.1157894736842104,
1239
+ "grad_norm": 7.342090129852295,
1240
+ "learning_rate": 4.2096631834319687e-07,
1241
+ "loss": 0.8627,
1242
+ "step": 1590
1243
+ },
1244
+ {
1245
+ "epoch": 1.1228070175438596,
1246
+ "grad_norm": 7.708263874053955,
1247
+ "learning_rate": 4.155289537036466e-07,
1248
+ "loss": 0.8916,
1249
+ "step": 1600
1250
+ },
1251
+ {
1252
+ "epoch": 1.1228070175438596,
1253
+ "eval_loss": 1.0080682039260864,
1254
+ "eval_runtime": 27.6601,
1255
+ "eval_samples_per_second": 173.535,
1256
+ "eval_steps_per_second": 2.711,
1257
+ "step": 1600
1258
+ },
1259
+ {
1260
+ "epoch": 1.1298245614035087,
1261
+ "grad_norm": 6.637975215911865,
1262
+ "learning_rate": 4.101018529898398e-07,
1263
+ "loss": 0.8598,
1264
+ "step": 1610
1265
+ },
1266
+ {
1267
+ "epoch": 1.1368421052631579,
1268
+ "grad_norm": 7.271252155303955,
1269
+ "learning_rate": 4.046856756390766e-07,
1270
+ "loss": 0.8632,
1271
+ "step": 1620
1272
+ },
1273
+ {
1274
+ "epoch": 1.143859649122807,
1275
+ "grad_norm": 6.89381742477417,
1276
+ "learning_rate": 3.99281079761379e-07,
1277
+ "loss": 0.8877,
1278
+ "step": 1630
1279
+ },
1280
+ {
1281
+ "epoch": 1.1508771929824562,
1282
+ "grad_norm": 7.032026290893555,
1283
+ "learning_rate": 3.938887220595252e-07,
1284
+ "loss": 0.879,
1285
+ "step": 1640
1286
+ },
1287
+ {
1288
+ "epoch": 1.1578947368421053,
1289
+ "grad_norm": 7.385174751281738,
1290
+ "learning_rate": 3.885092577492542e-07,
1291
+ "loss": 0.8893,
1292
+ "step": 1650
1293
+ },
1294
+ {
1295
+ "epoch": 1.1649122807017545,
1296
+ "grad_norm": 7.389017105102539,
1297
+ "learning_rate": 3.8314334047965207e-07,
1298
+ "loss": 0.8727,
1299
+ "step": 1660
1300
+ },
1301
+ {
1302
+ "epoch": 1.1719298245614036,
1303
+ "grad_norm": 6.653899192810059,
1304
+ "learning_rate": 3.7779162225372846e-07,
1305
+ "loss": 0.8941,
1306
+ "step": 1670
1307
+ },
1308
+ {
1309
+ "epoch": 1.1789473684210527,
1310
+ "grad_norm": 7.119126319885254,
1311
+ "learning_rate": 3.724547533491924e-07,
1312
+ "loss": 0.8676,
1313
+ "step": 1680
1314
+ },
1315
+ {
1316
+ "epoch": 1.1859649122807017,
1317
+ "grad_norm": 7.610691070556641,
1318
+ "learning_rate": 3.671333822394386e-07,
1319
+ "loss": 0.864,
1320
+ "step": 1690
1321
+ },
1322
+ {
1323
+ "epoch": 1.1929824561403508,
1324
+ "grad_norm": 6.851118564605713,
1325
+ "learning_rate": 3.6182815551475223e-07,
1326
+ "loss": 0.885,
1327
+ "step": 1700
1328
+ },
1329
+ {
1330
+ "epoch": 1.1929824561403508,
1331
+ "eval_loss": 1.0073468685150146,
1332
+ "eval_runtime": 27.66,
1333
+ "eval_samples_per_second": 173.536,
1334
+ "eval_steps_per_second": 2.712,
1335
+ "step": 1700
1336
+ },
1337
+ {
1338
+ "epoch": 1.2,
1339
+ "grad_norm": 7.08779764175415,
1340
+ "learning_rate": 3.565397178037429e-07,
1341
+ "loss": 0.875,
1342
+ "step": 1710
1343
+ },
1344
+ {
1345
+ "epoch": 1.207017543859649,
1346
+ "grad_norm": 6.938493728637695,
1347
+ "learning_rate": 3.5126871169501815e-07,
1348
+ "loss": 0.8823,
1349
+ "step": 1720
1350
+ },
1351
+ {
1352
+ "epoch": 1.2140350877192982,
1353
+ "grad_norm": 7.4112114906311035,
1354
+ "learning_rate": 3.4601577765910175e-07,
1355
+ "loss": 0.8428,
1356
+ "step": 1730
1357
+ },
1358
+ {
1359
+ "epoch": 1.2210526315789474,
1360
+ "grad_norm": 7.859072208404541,
1361
+ "learning_rate": 3.407815539706124e-07,
1362
+ "loss": 0.8659,
1363
+ "step": 1740
1364
+ },
1365
+ {
1366
+ "epoch": 1.2280701754385965,
1367
+ "grad_norm": 6.562801837921143,
1368
+ "learning_rate": 3.3556667663070835e-07,
1369
+ "loss": 0.8654,
1370
+ "step": 1750
1371
+ },
1372
+ {
1373
+ "epoch": 1.2350877192982457,
1374
+ "grad_norm": 7.658775806427002,
1375
+ "learning_rate": 3.303717792898073e-07,
1376
+ "loss": 0.8652,
1377
+ "step": 1760
1378
+ },
1379
+ {
1380
+ "epoch": 1.2421052631578948,
1381
+ "grad_norm": 7.275959491729736,
1382
+ "learning_rate": 3.2519749317059327e-07,
1383
+ "loss": 0.8957,
1384
+ "step": 1770
1385
+ },
1386
+ {
1387
+ "epoch": 1.2491228070175437,
1388
+ "grad_norm": 7.704782485961914,
1389
+ "learning_rate": 3.200444469913172e-07,
1390
+ "loss": 0.8737,
1391
+ "step": 1780
1392
+ },
1393
+ {
1394
+ "epoch": 1.256140350877193,
1395
+ "grad_norm": 7.395431995391846,
1396
+ "learning_rate": 3.1491326688940344e-07,
1397
+ "loss": 0.8542,
1398
+ "step": 1790
1399
+ },
1400
+ {
1401
+ "epoch": 1.263157894736842,
1402
+ "grad_norm": 6.88340425491333,
1403
+ "learning_rate": 3.0980457634536774e-07,
1404
+ "loss": 0.8843,
1405
+ "step": 1800
1406
+ },
1407
+ {
1408
+ "epoch": 1.263157894736842,
1409
+ "eval_loss": 1.0033657550811768,
1410
+ "eval_runtime": 27.6659,
1411
+ "eval_samples_per_second": 173.499,
1412
+ "eval_steps_per_second": 2.711,
1413
+ "step": 1800
1414
+ },
1415
+ {
1416
+ "epoch": 1.2701754385964912,
1417
+ "grad_norm": 6.7408766746521,
1418
+ "learning_rate": 3.0471899610706036e-07,
1419
+ "loss": 0.8331,
1420
+ "step": 1810
1421
+ },
1422
+ {
1423
+ "epoch": 1.2771929824561403,
1424
+ "grad_norm": 7.153403282165527,
1425
+ "learning_rate": 2.996571441142397e-07,
1426
+ "loss": 0.8465,
1427
+ "step": 1820
1428
+ },
1429
+ {
1430
+ "epoch": 1.2842105263157895,
1431
+ "grad_norm": 7.26017427444458,
1432
+ "learning_rate": 2.9461963542348733e-07,
1433
+ "loss": 0.8785,
1434
+ "step": 1830
1435
+ },
1436
+ {
1437
+ "epoch": 1.2912280701754386,
1438
+ "grad_norm": 7.271636486053467,
1439
+ "learning_rate": 2.896070821334736e-07,
1440
+ "loss": 0.8831,
1441
+ "step": 1840
1442
+ },
1443
+ {
1444
+ "epoch": 1.2982456140350878,
1445
+ "grad_norm": 6.8561201095581055,
1446
+ "learning_rate": 2.846200933105829e-07,
1447
+ "loss": 0.8578,
1448
+ "step": 1850
1449
+ },
1450
+ {
1451
+ "epoch": 1.305263157894737,
1452
+ "grad_norm": 7.387796878814697,
1453
+ "learning_rate": 2.7965927491490704e-07,
1454
+ "loss": 0.8439,
1455
+ "step": 1860
1456
+ },
1457
+ {
1458
+ "epoch": 1.312280701754386,
1459
+ "grad_norm": 7.401048183441162,
1460
+ "learning_rate": 2.747252297266162e-07,
1461
+ "loss": 0.8944,
1462
+ "step": 1870
1463
+ },
1464
+ {
1465
+ "epoch": 1.3192982456140352,
1466
+ "grad_norm": 7.2983527183532715,
1467
+ "learning_rate": 2.698185572727151e-07,
1468
+ "loss": 0.8689,
1469
+ "step": 1880
1470
+ },
1471
+ {
1472
+ "epoch": 1.3263157894736843,
1473
+ "grad_norm": 7.557769775390625,
1474
+ "learning_rate": 2.6493985375419775e-07,
1475
+ "loss": 0.885,
1476
+ "step": 1890
1477
+ },
1478
+ {
1479
+ "epoch": 1.3333333333333333,
1480
+ "grad_norm": 6.881629943847656,
1481
+ "learning_rate": 2.6008971197360175e-07,
1482
+ "loss": 0.8644,
1483
+ "step": 1900
1484
+ },
1485
+ {
1486
+ "epoch": 1.3333333333333333,
1487
+ "eval_loss": 1.0021144151687622,
1488
+ "eval_runtime": 27.6613,
1489
+ "eval_samples_per_second": 173.527,
1490
+ "eval_steps_per_second": 2.711,
1491
+ "step": 1900
1492
+ },
1493
+ {
1494
+ "epoch": 1.3403508771929824,
1495
+ "grad_norm": 7.333024978637695,
1496
+ "learning_rate": 2.5526872126297986e-07,
1497
+ "loss": 0.8912,
1498
+ "step": 1910
1499
+ },
1500
+ {
1501
+ "epoch": 1.3473684210526315,
1502
+ "grad_norm": 7.045767784118652,
1503
+ "learning_rate": 2.5047746741228977e-07,
1504
+ "loss": 0.8747,
1505
+ "step": 1920
1506
+ },
1507
+ {
1508
+ "epoch": 1.3543859649122807,
1509
+ "grad_norm": 7.227980613708496,
1510
+ "learning_rate": 2.457165325982169e-07,
1511
+ "loss": 0.8647,
1512
+ "step": 1930
1513
+ },
1514
+ {
1515
+ "epoch": 1.3614035087719298,
1516
+ "grad_norm": 7.303330898284912,
1517
+ "learning_rate": 2.4098649531343494e-07,
1518
+ "loss": 0.8657,
1519
+ "step": 1940
1520
+ },
1521
+ {
1522
+ "epoch": 1.368421052631579,
1523
+ "grad_norm": 7.276090621948242,
1524
+ "learning_rate": 2.362879302963135e-07,
1525
+ "loss": 0.8845,
1526
+ "step": 1950
1527
+ },
1528
+ {
1529
+ "epoch": 1.3754385964912281,
1530
+ "grad_norm": 7.321451663970947,
1531
+ "learning_rate": 2.3162140846108363e-07,
1532
+ "loss": 0.8487,
1533
+ "step": 1960
1534
+ },
1535
+ {
1536
+ "epoch": 1.3824561403508773,
1537
+ "grad_norm": 7.5262980461120605,
1538
+ "learning_rate": 2.2698749682846685e-07,
1539
+ "loss": 0.8762,
1540
+ "step": 1970
1541
+ },
1542
+ {
1543
+ "epoch": 1.3894736842105262,
1544
+ "grad_norm": 7.401157855987549,
1545
+ "learning_rate": 2.223867584567766e-07,
1546
+ "loss": 0.8748,
1547
+ "step": 1980
1548
+ },
1549
+ {
1550
+ "epoch": 1.3964912280701753,
1551
+ "grad_norm": 7.1058149337768555,
1552
+ "learning_rate": 2.1781975237350365e-07,
1553
+ "loss": 0.8641,
1554
+ "step": 1990
1555
+ },
1556
+ {
1557
+ "epoch": 1.4035087719298245,
1558
+ "grad_norm": 7.203502178192139,
1559
+ "learning_rate": 2.1328703350738765e-07,
1560
+ "loss": 0.8661,
1561
+ "step": 2000
1562
+ },
1563
+ {
1564
+ "epoch": 1.4035087719298245,
1565
+ "eval_loss": 1.000258445739746,
1566
+ "eval_runtime": 27.6622,
1567
+ "eval_samples_per_second": 173.522,
1568
+ "eval_steps_per_second": 2.711,
1569
+ "step": 2000
1570
+ },
1571
+ {
1572
+ "epoch": 1.4105263157894736,
1573
+ "grad_norm": 7.68574857711792,
1574
+ "learning_rate": 2.0878915262099096e-07,
1575
+ "loss": 0.8964,
1576
+ "step": 2010
1577
+ },
1578
+ {
1579
+ "epoch": 1.4175438596491228,
1580
+ "grad_norm": 7.339992523193359,
1581
+ "learning_rate": 2.0432665624377433e-07,
1582
+ "loss": 0.8779,
1583
+ "step": 2020
1584
+ },
1585
+ {
1586
+ "epoch": 1.424561403508772,
1587
+ "grad_norm": 7.711989879608154,
1588
+ "learning_rate": 1.999000866056908e-07,
1589
+ "loss": 0.8958,
1590
+ "step": 2030
1591
+ },
1592
+ {
1593
+ "epoch": 1.431578947368421,
1594
+ "grad_norm": 6.8218488693237305,
1595
+ "learning_rate": 1.9550998157129944e-07,
1596
+ "loss": 0.8848,
1597
+ "step": 2040
1598
+ },
1599
+ {
1600
+ "epoch": 1.4385964912280702,
1601
+ "grad_norm": 7.602545261383057,
1602
+ "learning_rate": 1.9115687457441022e-07,
1603
+ "loss": 0.8668,
1604
+ "step": 2050
1605
+ },
1606
+ {
1607
+ "epoch": 1.4456140350877194,
1608
+ "grad_norm": 7.199863433837891,
1609
+ "learning_rate": 1.8684129455326808e-07,
1610
+ "loss": 0.8705,
1611
+ "step": 2060
1612
+ },
1613
+ {
1614
+ "epoch": 1.4526315789473685,
1615
+ "grad_norm": 7.163413047790527,
1616
+ "learning_rate": 1.8256376588628235e-07,
1617
+ "loss": 0.8641,
1618
+ "step": 2070
1619
+ },
1620
+ {
1621
+ "epoch": 1.4596491228070176,
1622
+ "grad_norm": 7.178804397583008,
1623
+ "learning_rate": 1.7832480832830986e-07,
1624
+ "loss": 0.8526,
1625
+ "step": 2080
1626
+ },
1627
+ {
1628
+ "epoch": 1.4666666666666668,
1629
+ "grad_norm": 7.084789752960205,
1630
+ "learning_rate": 1.7412493694750173e-07,
1631
+ "loss": 0.8834,
1632
+ "step": 2090
1633
+ },
1634
+ {
1635
+ "epoch": 1.4736842105263157,
1636
+ "grad_norm": 7.647516250610352,
1637
+ "learning_rate": 1.6996466206271675e-07,
1638
+ "loss": 0.8712,
1639
+ "step": 2100
1640
+ },
1641
+ {
1642
+ "epoch": 1.4736842105263157,
1643
+ "eval_loss": 1.0002570152282715,
1644
+ "eval_runtime": 27.6725,
1645
+ "eval_samples_per_second": 173.457,
1646
+ "eval_steps_per_second": 2.71,
1647
+ "step": 2100
1648
+ },
1649
+ {
1650
+ "epoch": 1.4807017543859649,
1651
+ "grad_norm": 7.682786464691162,
1652
+ "learning_rate": 1.6584448918151518e-07,
1653
+ "loss": 0.8648,
1654
+ "step": 2110
1655
+ },
1656
+ {
1657
+ "epoch": 1.487719298245614,
1658
+ "grad_norm": 6.9408650398254395,
1659
+ "learning_rate": 1.6176491893873367e-07,
1660
+ "loss": 0.8775,
1661
+ "step": 2120
1662
+ },
1663
+ {
1664
+ "epoch": 1.4947368421052631,
1665
+ "grad_norm": 7.477031230926514,
1666
+ "learning_rate": 1.5772644703565564e-07,
1667
+ "loss": 0.8648,
1668
+ "step": 2130
1669
+ },
1670
+ {
1671
+ "epoch": 1.5017543859649123,
1672
+ "grad_norm": 7.054373741149902,
1673
+ "learning_rate": 1.537295641797785e-07,
1674
+ "loss": 0.8608,
1675
+ "step": 2140
1676
+ },
1677
+ {
1678
+ "epoch": 1.5087719298245614,
1679
+ "grad_norm": 6.98421049118042,
1680
+ "learning_rate": 1.4977475602518874e-07,
1681
+ "loss": 0.8653,
1682
+ "step": 2150
1683
+ },
1684
+ {
1685
+ "epoch": 1.5157894736842106,
1686
+ "grad_norm": 7.556164264678955,
1687
+ "learning_rate": 1.4586250311355132e-07,
1688
+ "loss": 0.8691,
1689
+ "step": 2160
1690
+ },
1691
+ {
1692
+ "epoch": 1.5228070175438595,
1693
+ "grad_norm": 7.721457004547119,
1694
+ "learning_rate": 1.4199328081572e-07,
1695
+ "loss": 0.8853,
1696
+ "step": 2170
1697
+ },
1698
+ {
1699
+ "epoch": 1.5298245614035086,
1700
+ "grad_norm": 7.5607428550720215,
1701
+ "learning_rate": 1.38167559273975e-07,
1702
+ "loss": 0.8647,
1703
+ "step": 2180
1704
+ },
1705
+ {
1706
+ "epoch": 1.5368421052631578,
1707
+ "grad_norm": 7.398414134979248,
1708
+ "learning_rate": 1.3438580334489818e-07,
1709
+ "loss": 0.8524,
1710
+ "step": 2190
1711
+ },
1712
+ {
1713
+ "epoch": 1.543859649122807,
1714
+ "grad_norm": 7.229887008666992,
1715
+ "learning_rate": 1.3064847254288796e-07,
1716
+ "loss": 0.8638,
1717
+ "step": 2200
1718
+ },
1719
+ {
1720
+ "epoch": 1.543859649122807,
1721
+ "eval_loss": 0.9979353547096252,
1722
+ "eval_runtime": 27.6809,
1723
+ "eval_samples_per_second": 173.405,
1724
+ "eval_steps_per_second": 2.709,
1725
+ "step": 2200
1726
+ },
1727
+ {
1728
+ "epoch": 1.550877192982456,
1729
+ "grad_norm": 7.479950428009033,
1730
+ "learning_rate": 1.26956020984325e-07,
1731
+ "loss": 0.8672,
1732
+ "step": 2210
1733
+ },
1734
+ {
1735
+ "epoch": 1.5578947368421052,
1736
+ "grad_norm": 7.526796340942383,
1737
+ "learning_rate": 1.2330889733239368e-07,
1738
+ "loss": 0.8882,
1739
+ "step": 2220
1740
+ },
1741
+ {
1742
+ "epoch": 1.5649122807017544,
1743
+ "grad_norm": 7.098681926727295,
1744
+ "learning_rate": 1.197075447425656e-07,
1745
+ "loss": 0.8564,
1746
+ "step": 2230
1747
+ },
1748
+ {
1749
+ "epoch": 1.5719298245614035,
1750
+ "grad_norm": 7.627535343170166,
1751
+ "learning_rate": 1.16152400808752e-07,
1752
+ "loss": 0.8778,
1753
+ "step": 2240
1754
+ },
1755
+ {
1756
+ "epoch": 1.5789473684210527,
1757
+ "grad_norm": 7.635378360748291,
1758
+ "learning_rate": 1.1264389751013325e-07,
1759
+ "loss": 0.8615,
1760
+ "step": 2250
1761
+ },
1762
+ {
1763
+ "epoch": 1.5859649122807018,
1764
+ "grad_norm": 7.256911754608154,
1765
+ "learning_rate": 1.0918246115866964e-07,
1766
+ "loss": 0.8828,
1767
+ "step": 2260
1768
+ },
1769
+ {
1770
+ "epoch": 1.592982456140351,
1771
+ "grad_norm": 7.054688453674316,
1772
+ "learning_rate": 1.0576851234730094e-07,
1773
+ "loss": 0.8602,
1774
+ "step": 2270
1775
+ },
1776
+ {
1777
+ "epoch": 1.6,
1778
+ "grad_norm": 7.2597479820251465,
1779
+ "learning_rate": 1.0240246589884045e-07,
1780
+ "loss": 0.8588,
1781
+ "step": 2280
1782
+ },
1783
+ {
1784
+ "epoch": 1.6070175438596492,
1785
+ "grad_norm": 7.462535381317139,
1786
+ "learning_rate": 9.90847308155715e-08,
1787
+ "loss": 0.8623,
1788
+ "step": 2290
1789
+ },
1790
+ {
1791
+ "epoch": 1.6140350877192984,
1792
+ "grad_norm": 7.354959487915039,
1793
+ "learning_rate": 9.581571022954987e-08,
1794
+ "loss": 0.8632,
1795
+ "step": 2300
1796
+ },
1797
+ {
1798
+ "epoch": 1.6140350877192984,
1799
+ "eval_loss": 0.9973437786102295,
1800
+ "eval_runtime": 27.6881,
1801
+ "eval_samples_per_second": 173.36,
1802
+ "eval_steps_per_second": 2.709,
1803
+ "step": 2300
1804
+ },
1805
+ {
1806
+ "epoch": 1.6210526315789475,
1807
+ "grad_norm": 7.283778667449951,
1808
+ "learning_rate": 9.259580135361927e-08,
1809
+ "loss": 0.8684,
1810
+ "step": 2310
1811
+ },
1812
+ {
1813
+ "epoch": 1.6280701754385964,
1814
+ "grad_norm": 7.570828914642334,
1815
+ "learning_rate": 8.942539543314798e-08,
1816
+ "loss": 0.8609,
1817
+ "step": 2320
1818
+ },
1819
+ {
1820
+ "epoch": 1.6350877192982456,
1821
+ "grad_norm": 7.366217613220215,
1822
+ "learning_rate": 8.630487769848876e-08,
1823
+ "loss": 0.8722,
1824
+ "step": 2330
1825
+ },
1826
+ {
1827
+ "epoch": 1.6421052631578947,
1828
+ "grad_norm": 7.667774200439453,
1829
+ "learning_rate": 8.32346273181696e-08,
1830
+ "loss": 0.8883,
1831
+ "step": 2340
1832
+ },
1833
+ {
1834
+ "epoch": 1.6491228070175439,
1835
+ "grad_norm": 8.111892700195312,
1836
+ "learning_rate": 8.021501735282266e-08,
1837
+ "loss": 0.8599,
1838
+ "step": 2350
1839
+ },
1840
+ {
1841
+ "epoch": 1.656140350877193,
1842
+ "grad_norm": 7.690216064453125,
1843
+ "learning_rate": 7.724641470985377e-08,
1844
+ "loss": 0.8951,
1845
+ "step": 2360
1846
+ },
1847
+ {
1848
+ "epoch": 1.663157894736842,
1849
+ "grad_norm": 7.080111980438232,
1850
+ "learning_rate": 7.432918009885996e-08,
1851
+ "loss": 0.865,
1852
+ "step": 2370
1853
+ },
1854
+ {
1855
+ "epoch": 1.670175438596491,
1856
+ "grad_norm": 7.580221176147461,
1857
+ "learning_rate": 7.146366798780096e-08,
1858
+ "loss": 0.8905,
1859
+ "step": 2380
1860
+ },
1861
+ {
1862
+ "epoch": 1.6771929824561402,
1863
+ "grad_norm": 6.910195827484131,
1864
+ "learning_rate": 6.865022655992798e-08,
1865
+ "loss": 0.8501,
1866
+ "step": 2390
1867
+ },
1868
+ {
1869
+ "epoch": 1.6842105263157894,
1870
+ "grad_norm": 7.176208972930908,
1871
+ "learning_rate": 6.588919767147638e-08,
1872
+ "loss": 0.8461,
1873
+ "step": 2400
1874
+ },
1875
+ {
1876
+ "epoch": 1.6842105263157894,
1877
+ "eval_loss": 0.9966626167297363,
1878
+ "eval_runtime": 27.668,
1879
+ "eval_samples_per_second": 173.486,
1880
+ "eval_steps_per_second": 2.711,
1881
+ "step": 2400
1882
+ },
1883
+ {
1884
+ "epoch": 1.6912280701754385,
1885
+ "grad_norm": 7.764338970184326,
1886
+ "learning_rate": 6.318091681012771e-08,
1887
+ "loss": 0.8711,
1888
+ "step": 2410
1889
+ },
1890
+ {
1891
+ "epoch": 1.6982456140350877,
1892
+ "grad_norm": 8.283316612243652,
1893
+ "learning_rate": 6.052571305424531e-08,
1894
+ "loss": 0.8738,
1895
+ "step": 2420
1896
+ },
1897
+ {
1898
+ "epoch": 1.7052631578947368,
1899
+ "grad_norm": 7.315950870513916,
1900
+ "learning_rate": 5.7923909032888295e-08,
1901
+ "loss": 0.8719,
1902
+ "step": 2430
1903
+ },
1904
+ {
1905
+ "epoch": 1.712280701754386,
1906
+ "grad_norm": 7.591914653778076,
1907
+ "learning_rate": 5.537582088660936e-08,
1908
+ "loss": 0.8708,
1909
+ "step": 2440
1910
+ },
1911
+ {
1912
+ "epoch": 1.719298245614035,
1913
+ "grad_norm": 7.378705978393555,
1914
+ "learning_rate": 5.2881758229041394e-08,
1915
+ "loss": 0.8722,
1916
+ "step": 2450
1917
+ },
1918
+ {
1919
+ "epoch": 1.7263157894736842,
1920
+ "grad_norm": 7.416294097900391,
1921
+ "learning_rate": 5.044202410927706e-08,
1922
+ "loss": 0.8586,
1923
+ "step": 2460
1924
+ },
1925
+ {
1926
+ "epoch": 1.7333333333333334,
1927
+ "grad_norm": 7.301969051361084,
1928
+ "learning_rate": 4.805691497504505e-08,
1929
+ "loss": 0.891,
1930
+ "step": 2470
1931
+ },
1932
+ {
1933
+ "epoch": 1.7403508771929825,
1934
+ "grad_norm": 6.946348190307617,
1935
+ "learning_rate": 4.5726720636690195e-08,
1936
+ "loss": 0.8871,
1937
+ "step": 2480
1938
+ },
1939
+ {
1940
+ "epoch": 1.7473684210526317,
1941
+ "grad_norm": 7.327394008636475,
1942
+ "learning_rate": 4.3451724231958645e-08,
1943
+ "loss": 0.8688,
1944
+ "step": 2490
1945
+ },
1946
+ {
1947
+ "epoch": 1.7543859649122808,
1948
+ "grad_norm": 7.17736291885376,
1949
+ "learning_rate": 4.123220219159418e-08,
1950
+ "loss": 0.8729,
1951
+ "step": 2500
1952
+ },
1953
+ {
1954
+ "epoch": 1.7543859649122808,
1955
+ "eval_loss": 0.9957481622695923,
1956
+ "eval_runtime": 27.665,
1957
+ "eval_samples_per_second": 173.504,
1958
+ "eval_steps_per_second": 2.711,
1959
+ "step": 2500
1960
+ }
1961
+ ],
1962
+ "logging_steps": 10,
1963
+ "max_steps": 2850,
1964
+ "num_input_tokens_seen": 0,
1965
+ "num_train_epochs": 2,
1966
+ "save_steps": 500,
1967
+ "total_flos": 6.354365204175782e+18,
1968
+ "train_batch_size": 4,
1969
+ "trial_name": null,
1970
+ "trial_params": null
1971
+ }
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ca3e521d51513c2dd80162960b65afc3921da4988a97a3cd9bf7abb5b74239db
3
+ size 6136
zero_to_fp32.py ADDED
@@ -0,0 +1,604 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ #!/usr/bin/env python
2
+
3
+ # Copyright (c) Microsoft Corporation.
4
+ # SPDX-License-Identifier: Apache-2.0
5
+
6
+ # DeepSpeed Team
7
+
8
+ # This script extracts fp32 consolidated weights from a zero 1, 2 and 3 DeepSpeed checkpoints. It gets
9
+ # copied into the top level checkpoint dir, so the user can easily do the conversion at any point in
10
+ # the future. Once extracted, the weights don't require DeepSpeed and can be used in any
11
+ # application.
12
+ #
13
+ # example: python zero_to_fp32.py . pytorch_model.bin
14
+
15
+ import argparse
16
+ import torch
17
+ import glob
18
+ import math
19
+ import os
20
+ import re
21
+ from collections import OrderedDict
22
+ from dataclasses import dataclass
23
+
24
+ # while this script doesn't use deepspeed to recover data, since the checkpoints are pickled with
25
+ # DeepSpeed data structures it has to be available in the current python environment.
26
+ from deepspeed.utils import logger
27
+ from deepspeed.checkpoint.constants import (DS_VERSION, OPTIMIZER_STATE_DICT, SINGLE_PARTITION_OF_FP32_GROUPS,
28
+ FP32_FLAT_GROUPS, ZERO_STAGE, PARTITION_COUNT, PARAM_SHAPES, BUFFER_NAMES,
29
+ FROZEN_PARAM_SHAPES, FROZEN_PARAM_FRAGMENTS)
30
+
31
+
32
+ @dataclass
33
+ class zero_model_state:
34
+ buffers: dict()
35
+ param_shapes: dict()
36
+ shared_params: list
37
+ ds_version: int
38
+ frozen_param_shapes: dict()
39
+ frozen_param_fragments: dict()
40
+
41
+
42
+ debug = 0
43
+
44
+ # load to cpu
45
+ device = torch.device('cpu')
46
+
47
+
48
+ def atoi(text):
49
+ return int(text) if text.isdigit() else text
50
+
51
+
52
+ def natural_keys(text):
53
+ '''
54
+ alist.sort(key=natural_keys) sorts in human order
55
+ http://nedbatchelder.com/blog/200712/human_sorting.html
56
+ (See Toothy's implementation in the comments)
57
+ '''
58
+ return [atoi(c) for c in re.split(r'(\d+)', text)]
59
+
60
+
61
+ def get_model_state_file(checkpoint_dir, zero_stage):
62
+ if not os.path.isdir(checkpoint_dir):
63
+ raise FileNotFoundError(f"Directory '{checkpoint_dir}' doesn't exist")
64
+
65
+ # there should be only one file
66
+ if zero_stage <= 2:
67
+ file = os.path.join(checkpoint_dir, "mp_rank_00_model_states.pt")
68
+ elif zero_stage == 3:
69
+ file = os.path.join(checkpoint_dir, "zero_pp_rank_0_mp_rank_00_model_states.pt")
70
+
71
+ if not os.path.exists(file):
72
+ raise FileNotFoundError(f"can't find model states file at '{file}'")
73
+
74
+ return file
75
+
76
+
77
+ def get_checkpoint_files(checkpoint_dir, glob_pattern):
78
+ # XXX: need to test that this simple glob rule works for multi-node setup too
79
+ ckpt_files = sorted(glob.glob(os.path.join(checkpoint_dir, glob_pattern)), key=natural_keys)
80
+
81
+ if len(ckpt_files) == 0:
82
+ raise FileNotFoundError(f"can't find {glob_pattern} files in directory '{checkpoint_dir}'")
83
+
84
+ return ckpt_files
85
+
86
+
87
+ def get_optim_files(checkpoint_dir):
88
+ return get_checkpoint_files(checkpoint_dir, "*_optim_states.pt")
89
+
90
+
91
+ def get_model_state_files(checkpoint_dir):
92
+ return get_checkpoint_files(checkpoint_dir, "*_model_states.pt")
93
+
94
+
95
+ def parse_model_states(files):
96
+ zero_model_states = []
97
+ for file in files:
98
+ state_dict = torch.load(file, map_location=device)
99
+
100
+ if BUFFER_NAMES not in state_dict:
101
+ raise ValueError(f"{file} is not a model state checkpoint")
102
+ buffer_names = state_dict[BUFFER_NAMES]
103
+ if debug:
104
+ print("Found buffers:", buffer_names)
105
+
106
+ # recover just the buffers while restoring them to fp32 if they were saved in fp16
107
+ buffers = {k: v.float() for k, v in state_dict["module"].items() if k in buffer_names}
108
+ param_shapes = state_dict[PARAM_SHAPES]
109
+
110
+ # collect parameters that are included in param_shapes
111
+ param_names = []
112
+ for s in param_shapes:
113
+ for name in s.keys():
114
+ param_names.append(name)
115
+
116
+ # update with frozen parameters
117
+ frozen_param_shapes = state_dict.get(FROZEN_PARAM_SHAPES, None)
118
+ if frozen_param_shapes is not None:
119
+ if debug:
120
+ print(f"Found frozen_param_shapes: {frozen_param_shapes}")
121
+ param_names += list(frozen_param_shapes.keys())
122
+
123
+ # handle shared params
124
+ shared_params = [[k, v] for k, v in state_dict["shared_params"].items()]
125
+
126
+ ds_version = state_dict.get(DS_VERSION, None)
127
+
128
+ frozen_param_fragments = state_dict.get(FROZEN_PARAM_FRAGMENTS, None)
129
+
130
+ z_model_state = zero_model_state(buffers=buffers,
131
+ param_shapes=param_shapes,
132
+ shared_params=shared_params,
133
+ ds_version=ds_version,
134
+ frozen_param_shapes=frozen_param_shapes,
135
+ frozen_param_fragments=frozen_param_fragments)
136
+ zero_model_states.append(z_model_state)
137
+
138
+ return zero_model_states
139
+
140
+
141
+ def parse_optim_states(files, ds_checkpoint_dir):
142
+
143
+ total_files = len(files)
144
+ state_dicts = []
145
+ for f in files:
146
+ state_dict = torch.load(f, map_location=device)
147
+ # immediately discard the potentially huge 2 optimizer states as we only care for fp32 master weights
148
+ # and also handle the case where it was already removed by another helper script
149
+ state_dict["optimizer_state_dict"].pop("optimizer_state_dict", None)
150
+ state_dicts.append(state_dict)
151
+
152
+ if not ZERO_STAGE in state_dicts[0][OPTIMIZER_STATE_DICT]:
153
+ raise ValueError(f"{files[0]} is not a zero checkpoint")
154
+ zero_stage = state_dicts[0][OPTIMIZER_STATE_DICT][ZERO_STAGE]
155
+ world_size = state_dicts[0][OPTIMIZER_STATE_DICT][PARTITION_COUNT]
156
+
157
+ # For ZeRO-2 each param group can have different partition_count as data parallelism for expert
158
+ # parameters can be different from data parallelism for non-expert parameters. So we can just
159
+ # use the max of the partition_count to get the dp world_size.
160
+
161
+ if type(world_size) is list:
162
+ world_size = max(world_size)
163
+
164
+ if world_size != total_files:
165
+ raise ValueError(
166
+ f"Expected {world_size} of '*_optim_states.pt' under '{ds_checkpoint_dir}' but found {total_files} files. "
167
+ "Possibly due to an overwrite of an old checkpoint, or a checkpoint didn't get saved by one or more processes."
168
+ )
169
+
170
+ # the groups are named differently in each stage
171
+ if zero_stage <= 2:
172
+ fp32_groups_key = SINGLE_PARTITION_OF_FP32_GROUPS
173
+ elif zero_stage == 3:
174
+ fp32_groups_key = FP32_FLAT_GROUPS
175
+ else:
176
+ raise ValueError(f"unknown zero stage {zero_stage}")
177
+
178
+ if zero_stage <= 2:
179
+ fp32_flat_groups = [state_dicts[i][OPTIMIZER_STATE_DICT][fp32_groups_key] for i in range(len(state_dicts))]
180
+ elif zero_stage == 3:
181
+ # if there is more than one param group, there will be multiple flattened tensors - one
182
+ # flattened tensor per group - for simplicity merge them into a single tensor
183
+ #
184
+ # XXX: could make the script more memory efficient for when there are multiple groups - it
185
+ # will require matching the sub-lists of param_shapes for each param group flattened tensor
186
+
187
+ fp32_flat_groups = [
188
+ torch.cat(state_dicts[i][OPTIMIZER_STATE_DICT][fp32_groups_key], 0) for i in range(len(state_dicts))
189
+ ]
190
+
191
+ return zero_stage, world_size, fp32_flat_groups
192
+
193
+
194
+ def _get_fp32_state_dict_from_zero_checkpoint(ds_checkpoint_dir, exclude_frozen_parameters):
195
+ """
196
+ Returns fp32 state_dict reconstructed from ds checkpoint
197
+
198
+ Args:
199
+ - ``ds_checkpoint_dir``: path to the deepspeed checkpoint folder (where the optimizer files are)
200
+
201
+ """
202
+ print(f"Processing zero checkpoint '{ds_checkpoint_dir}'")
203
+
204
+ optim_files = get_optim_files(ds_checkpoint_dir)
205
+ zero_stage, world_size, fp32_flat_groups = parse_optim_states(optim_files, ds_checkpoint_dir)
206
+ print(f"Detected checkpoint of type zero stage {zero_stage}, world_size: {world_size}")
207
+
208
+ model_files = get_model_state_files(ds_checkpoint_dir)
209
+
210
+ zero_model_states = parse_model_states(model_files)
211
+ print(f'Parsing checkpoint created by deepspeed=={zero_model_states[0].ds_version}')
212
+
213
+ if zero_stage <= 2:
214
+ return _get_fp32_state_dict_from_zero2_checkpoint(world_size, fp32_flat_groups, zero_model_states,
215
+ exclude_frozen_parameters)
216
+ elif zero_stage == 3:
217
+ return _get_fp32_state_dict_from_zero3_checkpoint(world_size, fp32_flat_groups, zero_model_states,
218
+ exclude_frozen_parameters)
219
+
220
+
221
+ def _zero2_merge_frozen_params(state_dict, zero_model_states):
222
+ if zero_model_states[0].frozen_param_shapes is None or len(zero_model_states[0].frozen_param_shapes) == 0:
223
+ return
224
+
225
+ frozen_param_shapes = zero_model_states[0].frozen_param_shapes
226
+ frozen_param_fragments = zero_model_states[0].frozen_param_fragments
227
+
228
+ if debug:
229
+ num_elem = sum(s.numel() for s in frozen_param_shapes.values())
230
+ print(f'rank 0: {FROZEN_PARAM_SHAPES}.numel = {num_elem}')
231
+
232
+ wanted_params = len(frozen_param_shapes)
233
+ wanted_numel = sum(s.numel() for s in frozen_param_shapes.values())
234
+ avail_numel = sum([p.numel() for p in frozen_param_fragments.values()])
235
+ print(f'Frozen params: Have {avail_numel} numels to process.')
236
+ print(f'Frozen params: Need {wanted_numel} numels in {wanted_params} params')
237
+
238
+ total_params = 0
239
+ total_numel = 0
240
+ for name, shape in frozen_param_shapes.items():
241
+ total_params += 1
242
+ unpartitioned_numel = shape.numel()
243
+ total_numel += unpartitioned_numel
244
+
245
+ state_dict[name] = frozen_param_fragments[name]
246
+
247
+ if debug:
248
+ print(f"{name} full shape: {shape} unpartitioned numel {unpartitioned_numel} ")
249
+
250
+ print(f"Reconstructed Frozen fp32 state dict with {total_params} params {total_numel} elements")
251
+
252
+
253
+ def _has_callable(obj, fn):
254
+ attr = getattr(obj, fn, None)
255
+ return callable(attr)
256
+
257
+
258
+ def _zero2_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states):
259
+ param_shapes = zero_model_states[0].param_shapes
260
+
261
+ # Reconstruction protocol:
262
+ #
263
+ # XXX: document this
264
+
265
+ if debug:
266
+ for i in range(world_size):
267
+ for j in range(len(fp32_flat_groups[0])):
268
+ print(f"{FP32_FLAT_GROUPS}[{i}][{j}].shape={fp32_flat_groups[i][j].shape}")
269
+
270
+ # XXX: memory usage doubles here (zero2)
271
+ num_param_groups = len(fp32_flat_groups[0])
272
+ merged_single_partition_of_fp32_groups = []
273
+ for i in range(num_param_groups):
274
+ merged_partitions = [sd[i] for sd in fp32_flat_groups]
275
+ full_single_fp32_vector = torch.cat(merged_partitions, 0)
276
+ merged_single_partition_of_fp32_groups.append(full_single_fp32_vector)
277
+ avail_numel = sum(
278
+ [full_single_fp32_vector.numel() for full_single_fp32_vector in merged_single_partition_of_fp32_groups])
279
+
280
+ if debug:
281
+ wanted_params = sum([len(shapes) for shapes in param_shapes])
282
+ wanted_numel = sum([sum(shape.numel() for shape in shapes.values()) for shapes in param_shapes])
283
+ # not asserting if there is a mismatch due to possible padding
284
+ print(f"Have {avail_numel} numels to process.")
285
+ print(f"Need {wanted_numel} numels in {wanted_params} params.")
286
+
287
+ # params
288
+ # XXX: for huge models that can't fit into the host's RAM we will have to recode this to support
289
+ # out-of-core computing solution
290
+ total_numel = 0
291
+ total_params = 0
292
+ for shapes, full_single_fp32_vector in zip(param_shapes, merged_single_partition_of_fp32_groups):
293
+ offset = 0
294
+ avail_numel = full_single_fp32_vector.numel()
295
+ for name, shape in shapes.items():
296
+
297
+ unpartitioned_numel = shape.numel() if _has_callable(shape, 'numel') else math.prod(shape)
298
+ total_numel += unpartitioned_numel
299
+ total_params += 1
300
+
301
+ if debug:
302
+ print(f"{name} full shape: {shape} unpartitioned numel {unpartitioned_numel} ")
303
+ state_dict[name] = full_single_fp32_vector.narrow(0, offset, unpartitioned_numel).view(shape)
304
+ offset += unpartitioned_numel
305
+
306
+ # Z2 started to align to 2*world_size to improve nccl performance. Therefore both offset and
307
+ # avail_numel can differ by anywhere between 0..2*world_size. Due to two unrelated complex
308
+ # paddings performed in the code it's almost impossible to predict the exact numbers w/o the
309
+ # live optimizer object, so we are checking that the numbers are within the right range
310
+ align_to = 2 * world_size
311
+
312
+ def zero2_align(x):
313
+ return align_to * math.ceil(x / align_to)
314
+
315
+ if debug:
316
+ print(f"original offset={offset}, avail_numel={avail_numel}")
317
+
318
+ offset = zero2_align(offset)
319
+ avail_numel = zero2_align(avail_numel)
320
+
321
+ if debug:
322
+ print(f"aligned offset={offset}, avail_numel={avail_numel}")
323
+
324
+ # Sanity check
325
+ if offset != avail_numel:
326
+ raise ValueError(f"consumed {offset} numels out of {avail_numel} - something is wrong")
327
+
328
+ print(f"Reconstructed fp32 state dict with {total_params} params {total_numel} elements")
329
+
330
+
331
+ def _get_fp32_state_dict_from_zero2_checkpoint(world_size, fp32_flat_groups, zero_model_states,
332
+ exclude_frozen_parameters):
333
+ state_dict = OrderedDict()
334
+
335
+ # buffers
336
+ buffers = zero_model_states[0].buffers
337
+ state_dict.update(buffers)
338
+ if debug:
339
+ print(f"added {len(buffers)} buffers")
340
+
341
+ if not exclude_frozen_parameters:
342
+ _zero2_merge_frozen_params(state_dict, zero_model_states)
343
+
344
+ _zero2_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states)
345
+
346
+ # recover shared parameters
347
+ for pair in zero_model_states[0].shared_params:
348
+ if pair[1] in state_dict:
349
+ state_dict[pair[0]] = state_dict[pair[1]]
350
+
351
+ return state_dict
352
+
353
+
354
+ def zero3_partitioned_param_info(unpartitioned_numel, world_size):
355
+ remainder = unpartitioned_numel % world_size
356
+ padding_numel = (world_size - remainder) if remainder else 0
357
+ partitioned_numel = math.ceil(unpartitioned_numel / world_size)
358
+ return partitioned_numel, padding_numel
359
+
360
+
361
+ def _zero3_merge_frozen_params(state_dict, world_size, zero_model_states):
362
+ if zero_model_states[0].frozen_param_shapes is None or len(zero_model_states[0].frozen_param_shapes) == 0:
363
+ return
364
+
365
+ if debug:
366
+ for i in range(world_size):
367
+ num_elem = sum(s.numel() for s in zero_model_states[i].frozen_param_fragments.values())
368
+ print(f'rank {i}: {FROZEN_PARAM_SHAPES}.numel = {num_elem}')
369
+
370
+ frozen_param_shapes = zero_model_states[0].frozen_param_shapes
371
+ wanted_params = len(frozen_param_shapes)
372
+ wanted_numel = sum(s.numel() for s in frozen_param_shapes.values())
373
+ avail_numel = sum([p.numel() for p in zero_model_states[0].frozen_param_fragments.values()]) * world_size
374
+ print(f'Frozen params: Have {avail_numel} numels to process.')
375
+ print(f'Frozen params: Need {wanted_numel} numels in {wanted_params} params')
376
+
377
+ total_params = 0
378
+ total_numel = 0
379
+ for name, shape in zero_model_states[0].frozen_param_shapes.items():
380
+ total_params += 1
381
+ unpartitioned_numel = shape.numel()
382
+ total_numel += unpartitioned_numel
383
+
384
+ param_frags = tuple(model_state.frozen_param_fragments[name] for model_state in zero_model_states)
385
+ state_dict[name] = torch.cat(param_frags, 0).narrow(0, 0, unpartitioned_numel).view(shape)
386
+
387
+ partitioned_numel, partitioned_padding_numel = zero3_partitioned_param_info(unpartitioned_numel, world_size)
388
+
389
+ if debug:
390
+ print(
391
+ f"Frozen params: {total_params} {name} full shape: {shape} partition0 numel={partitioned_numel} partitioned_padding_numel={partitioned_padding_numel}"
392
+ )
393
+
394
+ print(f"Reconstructed Frozen fp32 state dict with {total_params} params {total_numel} elements")
395
+
396
+
397
+ def _zero3_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states):
398
+ param_shapes = zero_model_states[0].param_shapes
399
+ avail_numel = fp32_flat_groups[0].numel() * world_size
400
+ # Reconstruction protocol: For zero3 we need to zip the partitions together at boundary of each
401
+ # param, re-consolidating each param, while dealing with padding if any
402
+
403
+ # merge list of dicts, preserving order
404
+ param_shapes = {k: v for d in param_shapes for k, v in d.items()}
405
+
406
+ if debug:
407
+ for i in range(world_size):
408
+ print(f"{FP32_FLAT_GROUPS}[{i}].shape={fp32_flat_groups[i].shape}")
409
+
410
+ wanted_params = len(param_shapes)
411
+ wanted_numel = sum(shape.numel() for shape in param_shapes.values())
412
+ # not asserting if there is a mismatch due to possible padding
413
+ avail_numel = fp32_flat_groups[0].numel() * world_size
414
+ print(f"Trainable params: Have {avail_numel} numels to process.")
415
+ print(f"Trainable params: Need {wanted_numel} numels in {wanted_params} params.")
416
+
417
+ # params
418
+ # XXX: for huge models that can't fit into the host's RAM we will have to recode this to support
419
+ # out-of-core computing solution
420
+ offset = 0
421
+ total_numel = 0
422
+ total_params = 0
423
+ for name, shape in param_shapes.items():
424
+
425
+ unpartitioned_numel = shape.numel()
426
+ total_numel += unpartitioned_numel
427
+ total_params += 1
428
+
429
+ partitioned_numel, partitioned_padding_numel = zero3_partitioned_param_info(unpartitioned_numel, world_size)
430
+
431
+ if debug:
432
+ print(
433
+ f"Trainable params: {total_params} {name} full shape: {shape} partition0 numel={partitioned_numel} partitioned_padding_numel={partitioned_padding_numel}"
434
+ )
435
+
436
+ # XXX: memory usage doubles here
437
+ state_dict[name] = torch.cat(
438
+ tuple(fp32_flat_groups[i].narrow(0, offset, partitioned_numel) for i in range(world_size)),
439
+ 0).narrow(0, 0, unpartitioned_numel).view(shape)
440
+ offset += partitioned_numel
441
+
442
+ offset *= world_size
443
+
444
+ # Sanity check
445
+ if offset != avail_numel:
446
+ raise ValueError(f"consumed {offset} numels out of {avail_numel} - something is wrong")
447
+
448
+ print(f"Reconstructed Trainable fp32 state dict with {total_params} params {total_numel} elements")
449
+
450
+
451
+ def _get_fp32_state_dict_from_zero3_checkpoint(world_size, fp32_flat_groups, zero_model_states,
452
+ exclude_frozen_parameters):
453
+ state_dict = OrderedDict()
454
+
455
+ # buffers
456
+ buffers = zero_model_states[0].buffers
457
+ state_dict.update(buffers)
458
+ if debug:
459
+ print(f"added {len(buffers)} buffers")
460
+
461
+ if not exclude_frozen_parameters:
462
+ _zero3_merge_frozen_params(state_dict, world_size, zero_model_states)
463
+
464
+ _zero3_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states)
465
+
466
+ # recover shared parameters
467
+ for pair in zero_model_states[0].shared_params:
468
+ if pair[1] in state_dict:
469
+ state_dict[pair[0]] = state_dict[pair[1]]
470
+
471
+ return state_dict
472
+
473
+
474
+ def get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir, tag=None, exclude_frozen_parameters=False):
475
+ """
476
+ Convert ZeRO 2 or 3 checkpoint into a single fp32 consolidated state_dict that can be loaded with
477
+ ``load_state_dict()`` and used for training without DeepSpeed or shared with others, for example
478
+ via a model hub.
479
+
480
+ Args:
481
+ - ``checkpoint_dir``: path to the desired checkpoint folder
482
+ - ``tag``: checkpoint tag used as a unique identifier for checkpoint. If not provided will attempt to load tag in 'latest' file. e.g., ``global_step14``
483
+ - ``exclude_frozen_parameters``: exclude frozen parameters
484
+
485
+ Returns:
486
+ - pytorch ``state_dict``
487
+
488
+ Note: this approach may not work if your application doesn't have sufficient free CPU memory and
489
+ you may need to use the offline approach using the ``zero_to_fp32.py`` script that is saved with
490
+ the checkpoint.
491
+
492
+ A typical usage might be ::
493
+
494
+ from deepspeed.utils.zero_to_fp32 import get_fp32_state_dict_from_zero_checkpoint
495
+ # do the training and checkpoint saving
496
+ state_dict = get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir) # already on cpu
497
+ model = model.cpu() # move to cpu
498
+ model.load_state_dict(state_dict)
499
+ # submit to model hub or save the model to share with others
500
+
501
+ In this example the ``model`` will no longer be usable in the deepspeed context of the same
502
+ application. i.e. you will need to re-initialize the deepspeed engine, since
503
+ ``model.load_state_dict(state_dict)`` will remove all the deepspeed magic from it.
504
+
505
+ If you want it all done for you, use ``load_state_dict_from_zero_checkpoint`` instead.
506
+
507
+ """
508
+ if tag is None:
509
+ latest_path = os.path.join(checkpoint_dir, 'latest')
510
+ if os.path.isfile(latest_path):
511
+ with open(latest_path, 'r') as fd:
512
+ tag = fd.read().strip()
513
+ else:
514
+ raise ValueError(f"Unable to find 'latest' file at {latest_path}")
515
+
516
+ ds_checkpoint_dir = os.path.join(checkpoint_dir, tag)
517
+
518
+ if not os.path.isdir(ds_checkpoint_dir):
519
+ raise FileNotFoundError(f"Directory '{ds_checkpoint_dir}' doesn't exist")
520
+
521
+ return _get_fp32_state_dict_from_zero_checkpoint(ds_checkpoint_dir, exclude_frozen_parameters)
522
+
523
+
524
+ def convert_zero_checkpoint_to_fp32_state_dict(checkpoint_dir, output_file, tag=None, exclude_frozen_parameters=False):
525
+ """
526
+ Convert ZeRO 2 or 3 checkpoint into a single fp32 consolidated ``state_dict`` file that can be
527
+ loaded with ``torch.load(file)`` + ``load_state_dict()`` and used for training without DeepSpeed.
528
+
529
+ Args:
530
+ - ``checkpoint_dir``: path to the desired checkpoint folder. (one that contains the tag-folder, like ``global_step14``)
531
+ - ``output_file``: path to the pytorch fp32 state_dict output file (e.g. path/pytorch_model.bin)
532
+ - ``tag``: checkpoint tag used as a unique identifier for checkpoint. If not provided will attempt to load tag in the file named ``latest`` in the checkpoint folder, e.g., ``global_step14``
533
+ - ``exclude_frozen_parameters``: exclude frozen parameters
534
+ """
535
+
536
+ state_dict = get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir, tag, exclude_frozen_parameters)
537
+ print(f"Saving fp32 state dict to {output_file}")
538
+ torch.save(state_dict, output_file)
539
+
540
+
541
+ def load_state_dict_from_zero_checkpoint(model, checkpoint_dir, tag=None):
542
+ """
543
+ 1. Put the provided model to cpu
544
+ 2. Convert ZeRO 2 or 3 checkpoint into a single fp32 consolidated ``state_dict``
545
+ 3. Load it into the provided model
546
+
547
+ Args:
548
+ - ``model``: the model object to update
549
+ - ``checkpoint_dir``: path to the desired checkpoint folder. (one that contains the tag-folder, like ``global_step14``)
550
+ - ``tag``: checkpoint tag used as a unique identifier for checkpoint. If not provided will attempt to load tag in the file named ``latest`` in the checkpoint folder, e.g., ``global_step14``
551
+
552
+ Returns:
553
+ - ``model`: modified model
554
+
555
+ Make sure you have plenty of CPU memory available before you call this function. If you don't
556
+ have enough use the ``zero_to_fp32.py`` utility to do the conversion. You will find it
557
+ conveniently placed for you in the checkpoint folder.
558
+
559
+ A typical usage might be ::
560
+
561
+ from deepspeed.utils.zero_to_fp32 import load_state_dict_from_zero_checkpoint
562
+ model = load_state_dict_from_zero_checkpoint(trainer.model, checkpoint_dir)
563
+ # submit to model hub or save the model to share with others
564
+
565
+ Note, that once this was run, the ``model`` will no longer be usable in the deepspeed context
566
+ of the same application. i.e. you will need to re-initialize the deepspeed engine, since
567
+ ``model.load_state_dict(state_dict)`` will remove all the deepspeed magic from it.
568
+
569
+ """
570
+ logger.info(f"Extracting fp32 weights")
571
+ state_dict = get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir, tag)
572
+
573
+ logger.info(f"Overwriting model with fp32 weights")
574
+ model = model.cpu()
575
+ model.load_state_dict(state_dict, strict=False)
576
+
577
+ return model
578
+
579
+
580
+ if __name__ == "__main__":
581
+
582
+ parser = argparse.ArgumentParser()
583
+ parser.add_argument("checkpoint_dir",
584
+ type=str,
585
+ help="path to the desired checkpoint folder, e.g., path/checkpoint-12")
586
+ parser.add_argument(
587
+ "output_file",
588
+ type=str,
589
+ help="path to the pytorch fp32 state_dict output file (e.g. path/checkpoint-12/pytorch_model.bin)")
590
+ parser.add_argument("-t",
591
+ "--tag",
592
+ type=str,
593
+ default=None,
594
+ help="checkpoint tag used as a unique identifier for checkpoint. e.g., global_step1")
595
+ parser.add_argument("--exclude_frozen_parameters", action='store_true', help="exclude frozen parameters")
596
+ parser.add_argument("-d", "--debug", action='store_true', help="enable debug")
597
+ args = parser.parse_args()
598
+
599
+ debug = args.debug
600
+
601
+ convert_zero_checkpoint_to_fp32_state_dict(args.checkpoint_dir,
602
+ args.output_file,
603
+ tag=args.tag,
604
+ exclude_frozen_parameters=args.exclude_frozen_parameters)