Hugging Face's logo

ugaoo
/
model_ab12804a

PEFT
Safetensors
llama
Generated from Trainer
4-bit precision
bitsandbytes
Model card Files
xet
Community
ugaoo commited on
Commit
5ce319f
·
verified ·
1 Parent(s): bd68ce4

Upload folder using huggingface_hub

Browse files
Files changed (31) hide show
  1. README.md +143 -0
  2. adapter_config.json +1 -1
  3. adapter_model.safetensors +3 -0
  4. checkpoint-360/README.md +202 -0
  5. checkpoint-360/adapter_config.json +40 -0
  6. checkpoint-360/adapter_model.safetensors +3 -0
  7. checkpoint-360/global_step360/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt +3 -0
  8. checkpoint-360/global_step360/mp_rank_00_model_states.pt +3 -0
  9. checkpoint-360/latest +1 -0
  10. checkpoint-360/rng_state.pth +3 -0
  11. checkpoint-360/scheduler.pt +3 -0
  12. checkpoint-360/special_tokens_map.json +23 -0
  13. checkpoint-360/tokenizer.json +3 -0
  14. checkpoint-360/tokenizer_config.json +2064 -0
  15. checkpoint-360/trainer_state.json +2553 -0
  16. checkpoint-360/training_args.bin +3 -0
  17. checkpoint-360/zero_to_fp32.py +604 -0
  18. checkpoint-432/README.md +202 -0
  19. checkpoint-432/adapter_config.json +40 -0
  20. checkpoint-432/adapter_model.safetensors +3 -0
  21. checkpoint-432/global_step432/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt +3 -0
  22. checkpoint-432/global_step432/mp_rank_00_model_states.pt +3 -0
  23. checkpoint-432/latest +1 -0
  24. checkpoint-432/rng_state.pth +3 -0
  25. checkpoint-432/scheduler.pt +3 -0
  26. checkpoint-432/special_tokens_map.json +23 -0
  27. checkpoint-432/tokenizer.json +3 -0
  28. checkpoint-432/tokenizer_config.json +2064 -0
  29. checkpoint-432/trainer_state.json +3057 -0
  30. checkpoint-432/training_args.bin +3 -0
  31. checkpoint-432/zero_to_fp32.py +604 -0
README.md ADDED
@@ -0,0 +1,143 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ license: llama3.1
4
+ base_model: meta-llama/Llama-3.1-8B-Instruct
5
+ tags:
6
+ - generated_from_trainer
7
+ datasets:
8
+ - ugaoo/pubmedqa_train
9
+ model-index:
10
+ - name: out/meta_llama_Llama_3.1_8B_Instruct_ugaoo_pubmedqa_train
11
+ results: []
12
+ ---
13
+
14
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
15
+ should probably proofread and complete it, then remove this comment. -->
16
+
17
+ [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
18
+ <details><summary>See axolotl config</summary>
19
+
20
+ axolotl version: `0.8.0.dev0`
21
+ ```yaml
22
+ base_model: meta-llama/Llama-3.1-8B-Instruct
23
+ model_type: AutoModelForCausalLM
24
+ tokenizer_type: AutoTokenizer
25
+ trust_remote_code: true
26
+
27
+ load_in_8bit: false
28
+ load_in_4bit: true
29
+ strict: false
30
+
31
+ datasets:
32
+ - path: ugaoo/pubmedqa_train
33
+ type: alpaca
34
+ val_set_size: 0
35
+ output_dir: ./out/meta_llama_Llama_3.1_8B_Instruct_ugaoo_pubmedqa_train
36
+
37
+ sequence_len: 4000
38
+ sample_packing: true
39
+ pad_to_sequence_len: true
40
+
41
+ adapter: qlora
42
+ lora_r: 256
43
+ lora_alpha: 512
44
+ lora_dropout: 0.05
45
+ lora_target_linear: true
46
+ lora_target_modules:
47
+ - q_proj
48
+ - k_proj
49
+ - v_proj
50
+ - o_proj
51
+ - up_proj
52
+ - down_proj
53
+ - gate_proj
54
+ lora_modules_to_save:
55
+ - embed_tokens
56
+ - lm_head
57
+
58
+ wandb_project: testsearch
59
+ wandb_entity:
60
+ wandb_watch:
61
+ wandb_name: meta_llama_Llama_3.1_8B_Instruct_ugaoo_pubmedqa_train
62
+ wandb_log_model:
63
+
64
+ gradient_accumulation_steps: 3
65
+ micro_batch_size: 4
66
+ num_epochs: 6
67
+ optimizer: adamw_torch
68
+ lr_scheduler: cosine
69
+ learning_rate: 5e-6
70
+
71
+ train_on_inputs: false
72
+ group_by_length: false
73
+ bf16: auto
74
+ fp16: false
75
+ tf32: false
76
+
77
+ gradient_checkpointing: true
78
+ early_stopping_patience:
79
+ resume_from_checkpoint:
80
+ logging_steps: 1
81
+ xformers_attention:
82
+ flash_attention: true
83
+
84
+ warmup_steps: 100
85
+ evals_per_epoch: 6
86
+ eval_table_size:
87
+ saves_per_epoch: 1
88
+ debug:
89
+ deepspeed:
90
+ weight_decay: 0.0
91
+ fsdp:
92
+ fsdp_config:
93
+ save_total_limit: 6
94
+ special_tokens:
95
+ pad_token: <|end_of_text|>
96
+ ```
97
+
98
+ </details><br>
99
+
100
+ # out/meta_llama_Llama_3.1_8B_Instruct_ugaoo_pubmedqa_train
101
+
102
+ This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on the ugaoo/pubmedqa_train dataset.
103
+
104
+ ## Model description
105
+
106
+ More information needed
107
+
108
+ ## Intended uses & limitations
109
+
110
+ More information needed
111
+
112
+ ## Training and evaluation data
113
+
114
+ More information needed
115
+
116
+ ## Training procedure
117
+
118
+ ### Training hyperparameters
119
+
120
+ The following hyperparameters were used during training:
121
+ - learning_rate: 5e-06
122
+ - train_batch_size: 4
123
+ - eval_batch_size: 4
124
+ - seed: 42
125
+ - distributed_type: multi-GPU
126
+ - gradient_accumulation_steps: 3
127
+ - total_train_batch_size: 12
128
+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
129
+ - lr_scheduler_type: cosine
130
+ - lr_scheduler_warmup_steps: 100
131
+ - num_epochs: 6.0
132
+
133
+ ### Training results
134
+
135
+
136
+
137
+ ### Framework versions
138
+
139
+ - PEFT 0.14.0
140
+ - Transformers 4.49.0
141
+ - Pytorch 2.5.1+cu124
142
+ - Datasets 3.2.0
143
+ - Tokenizers 0.21.0
adapter_config.json CHANGED
@@ -6,7 +6,7 @@
6
  "eva_config": null,
7
  "exclude_modules": null,
8
  "fan_in_fan_out": null,
9
- "inference_mode": false,
10
  "init_lora_weights": true,
11
  "layer_replication": null,
12
  "layers_pattern": null,
 
6
  "eva_config": null,
7
  "exclude_modules": null,
8
  "fan_in_fan_out": null,
9
+ "inference_mode": true,
10
  "init_lora_weights": true,
11
  "layer_replication": null,
12
  "layers_pattern": null,
adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f3f83e1c7b18523e50c33645a557501eb084d15f1f696abb2cf911bb7c9306dc
3
+ size 3443586272
checkpoint-360/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: meta-llama/Llama-3.1-8B-Instruct
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.14.0
checkpoint-360/adapter_config.json ADDED
@@ -0,0 +1,40 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "meta-llama/Llama-3.1-8B-Instruct",
5
+ "bias": "none",
6
+ "eva_config": null,
7
+ "exclude_modules": null,
8
+ "fan_in_fan_out": null,
9
+ "inference_mode": true,
10
+ "init_lora_weights": true,
11
+ "layer_replication": null,
12
+ "layers_pattern": null,
13
+ "layers_to_transform": null,
14
+ "loftq_config": {},
15
+ "lora_alpha": 512,
16
+ "lora_bias": false,
17
+ "lora_dropout": 0.05,
18
+ "megatron_config": null,
19
+ "megatron_core": "megatron.core",
20
+ "modules_to_save": [
21
+ "embed_tokens",
22
+ "lm_head"
23
+ ],
24
+ "peft_type": "LORA",
25
+ "r": 256,
26
+ "rank_pattern": {},
27
+ "revision": null,
28
+ "target_modules": [
29
+ "o_proj",
30
+ "gate_proj",
31
+ "up_proj",
32
+ "q_proj",
33
+ "k_proj",
34
+ "down_proj",
35
+ "v_proj"
36
+ ],
37
+ "task_type": "CAUSAL_LM",
38
+ "use_dora": false,
39
+ "use_rslora": false
40
+ }
checkpoint-360/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:bde666e7072ac07a2bd4a30d034761377b5b8ae8ac9d7d5b56fe2b0c4a00e0e0
3
+ size 3443586272
checkpoint-360/global_step360/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:24aa93cc3967a278bc630bed210c984eca2be3dec87bb60c3f16ace21fcdaa6e
3
+ size 20661195036
checkpoint-360/global_step360/mp_rank_00_model_states.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:3d4c2ae9ce679de61566b43381651c0959751132c2fb2c60cbccea074d194eb9
3
+ size 3555326649
checkpoint-360/latest ADDED
@@ -0,0 +1 @@
 
 
1
+ global_step360
checkpoint-360/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:229bd577af76a9537d604f29baaa6dca841e24a4887c603c008aa6e00e3cc8db
3
+ size 14244
checkpoint-360/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f12fb5515df7dcf4cc1a3ecda848613d64db62cd311a9066dc53c01e4e1c6a83
3
+ size 1064
checkpoint-360/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": "<|end_of_text|>",
18
+ "lstrip": false,
19
+ "normalized": false,
20
+ "rstrip": false,
21
+ "single_word": false
22
+ }
23
+ }
checkpoint-360/tokenizer.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6b9e4e7fb171f92fd137b777cc2714bf87d11576700a1dcd7a399e7bbe39537b
3
+ size 17209920
checkpoint-360/tokenizer_config.json ADDED
@@ -0,0 +1,2064 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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": "<|finetune_right_pad_id|>",
37
+ "lstrip": false,
38
+ "normalized": false,
39
+ "rstrip": false,
40
+ "single_word": false,
41
+ "special": true
42
+ },
43
+ "128005": {
44
+ "content": "<|reserved_special_token_2|>",
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": "<|eom_id|>",
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": "<|python_tag|>",
85
+ "lstrip": false,
86
+ "normalized": false,
87
+ "rstrip": false,
88
+ "single_word": false,
89
+ "special": true
90
+ },
91
+ "128011": {
92
+ "content": "<|reserved_special_token_3|>",
93
+ "lstrip": false,
94
+ "normalized": false,
95
+ "rstrip": false,
96
+ "single_word": false,
97
+ "special": true
98
+ },
99
+ "128012": {
100
+ "content": "<|reserved_special_token_4|>",
101
+ "lstrip": false,
102
+ "normalized": false,
103
+ "rstrip": false,
104
+ "single_word": false,
105
+ "special": true
106
+ },
107
+ "128013": {
108
+ "content": "<|reserved_special_token_5|>",
109
+ "lstrip": false,
110
+ "normalized": false,
111
+ "rstrip": false,
112
+ "single_word": false,
113
+ "special": true
114
+ },
115
+ "128014": {
116
+ "content": "<|reserved_special_token_6|>",
117
+ "lstrip": false,
118
+ "normalized": false,
119
+ "rstrip": false,
120
+ "single_word": false,
121
+ "special": true
122
+ },
123
+ "128015": {
124
+ "content": "<|reserved_special_token_7|>",
125
+ "lstrip": false,
126
+ "normalized": false,
127
+ "rstrip": false,
128
+ "single_word": false,
129
+ "special": true
130
+ },
131
+ "128016": {
132
+ "content": "<|reserved_special_token_8|>",
133
+ "lstrip": false,
134
+ "normalized": false,
135
+ "rstrip": false,
136
+ "single_word": false,
137
+ "special": true
138
+ },
139
+ "128017": {
140
+ "content": "<|reserved_special_token_9|>",
141
+ "lstrip": false,
142
+ "normalized": false,
143
+ "rstrip": false,
144
+ "single_word": false,
145
+ "special": true
146
+ },
147
+ "128018": {
148
+ "content": "<|reserved_special_token_10|>",
149
+ "lstrip": false,
150
+ "normalized": false,
151
+ "rstrip": false,
152
+ "single_word": false,
153
+ "special": true
154
+ },
155
+ "128019": {
156
+ "content": "<|reserved_special_token_11|>",
157
+ "lstrip": false,
158
+ "normalized": false,
159
+ "rstrip": false,
160
+ "single_word": false,
161
+ "special": true
162
+ },
163
+ "128020": {
164
+ "content": "<|reserved_special_token_12|>",
165
+ "lstrip": false,
166
+ "normalized": false,
167
+ "rstrip": false,
168
+ "single_word": false,
169
+ "special": true
170
+ },
171
+ "128021": {
172
+ "content": "<|reserved_special_token_13|>",
173
+ "lstrip": false,
174
+ "normalized": false,
175
+ "rstrip": false,
176
+ "single_word": false,
177
+ "special": true
178
+ },
179
+ "128022": {
180
+ "content": "<|reserved_special_token_14|>",
181
+ "lstrip": false,
182
+ "normalized": false,
183
+ "rstrip": false,
184
+ "single_word": false,
185
+ "special": true
186
+ },
187
+ "128023": {
188
+ "content": "<|reserved_special_token_15|>",
189
+ "lstrip": false,
190
+ "normalized": false,
191
+ "rstrip": false,
192
+ "single_word": false,
193
+ "special": true
194
+ },
195
+ "128024": {
196
+ "content": "<|reserved_special_token_16|>",
197
+ "lstrip": false,
198
+ "normalized": false,
199
+ "rstrip": false,
200
+ "single_word": false,
201
+ "special": true
202
+ },
203
+ "128025": {
204
+ "content": "<|reserved_special_token_17|>",
205
+ "lstrip": false,
206
+ "normalized": false,
207
+ "rstrip": false,
208
+ "single_word": false,
209
+ "special": true
210
+ },
211
+ "128026": {
212
+ "content": "<|reserved_special_token_18|>",
213
+ "lstrip": false,
214
+ "normalized": false,
215
+ "rstrip": false,
216
+ "single_word": false,
217
+ "special": true
218
+ },
219
+ "128027": {
220
+ "content": "<|reserved_special_token_19|>",
221
+ "lstrip": false,
222
+ "normalized": false,
223
+ "rstrip": false,
224
+ "single_word": false,
225
+ "special": true
226
+ },
227
+ "128028": {
228
+ "content": "<|reserved_special_token_20|>",
229
+ "lstrip": false,
230
+ "normalized": false,
231
+ "rstrip": false,
232
+ "single_word": false,
233
+ "special": true
234
+ },
235
+ "128029": {
236
+ "content": "<|reserved_special_token_21|>",
237
+ "lstrip": false,
238
+ "normalized": false,
239
+ "rstrip": false,
240
+ "single_word": false,
241
+ "special": true
242
+ },
243
+ "128030": {
244
+ "content": "<|reserved_special_token_22|>",
245
+ "lstrip": false,
246
+ "normalized": false,
247
+ "rstrip": false,
248
+ "single_word": false,
249
+ "special": true
250
+ },
251
+ "128031": {
252
+ "content": "<|reserved_special_token_23|>",
253
+ "lstrip": false,
254
+ "normalized": false,
255
+ "rstrip": false,
256
+ "single_word": false,
257
+ "special": true
258
+ },
259
+ "128032": {
260
+ "content": "<|reserved_special_token_24|>",
261
+ "lstrip": false,
262
+ "normalized": false,
263
+ "rstrip": false,
264
+ "single_word": false,
265
+ "special": true
266
+ },
267
+ "128033": {
268
+ "content": "<|reserved_special_token_25|>",
269
+ "lstrip": false,
270
+ "normalized": false,
271
+ "rstrip": false,
272
+ "single_word": false,
273
+ "special": true
274
+ },
275
+ "128034": {
276
+ "content": "<|reserved_special_token_26|>",
277
+ "lstrip": false,
278
+ "normalized": false,
279
+ "rstrip": false,
280
+ "single_word": false,
281
+ "special": true
282
+ },
283
+ "128035": {
284
+ "content": "<|reserved_special_token_27|>",
285
+ "lstrip": false,
286
+ "normalized": false,
287
+ "rstrip": false,
288
+ "single_word": false,
289
+ "special": true
290
+ },
291
+ "128036": {
292
+ "content": "<|reserved_special_token_28|>",
293
+ "lstrip": false,
294
+ "normalized": false,
295
+ "rstrip": false,
296
+ "single_word": false,
297
+ "special": true
298
+ },
299
+ "128037": {
300
+ "content": "<|reserved_special_token_29|>",
301
+ "lstrip": false,
302
+ "normalized": false,
303
+ "rstrip": false,
304
+ "single_word": false,
305
+ "special": true
306
+ },
307
+ "128038": {
308
+ "content": "<|reserved_special_token_30|>",
309
+ "lstrip": false,
310
+ "normalized": false,
311
+ "rstrip": false,
312
+ "single_word": false,
313
+ "special": true
314
+ },
315
+ "128039": {
316
+ "content": "<|reserved_special_token_31|>",
317
+ "lstrip": false,
318
+ "normalized": false,
319
+ "rstrip": false,
320
+ "single_word": false,
321
+ "special": true
322
+ },
323
+ "128040": {
324
+ "content": "<|reserved_special_token_32|>",
325
+ "lstrip": false,
326
+ "normalized": false,
327
+ "rstrip": false,
328
+ "single_word": false,
329
+ "special": true
330
+ },
331
+ "128041": {
332
+ "content": "<|reserved_special_token_33|>",
333
+ "lstrip": false,
334
+ "normalized": false,
335
+ "rstrip": false,
336
+ "single_word": false,
337
+ "special": true
338
+ },
339
+ "128042": {
340
+ "content": "<|reserved_special_token_34|>",
341
+ "lstrip": false,
342
+ "normalized": false,
343
+ "rstrip": false,
344
+ "single_word": false,
345
+ "special": true
346
+ },
347
+ "128043": {
348
+ "content": "<|reserved_special_token_35|>",
349
+ "lstrip": false,
350
+ "normalized": false,
351
+ "rstrip": false,
352
+ "single_word": false,
353
+ "special": true
354
+ },
355
+ "128044": {
356
+ "content": "<|reserved_special_token_36|>",
357
+ "lstrip": false,
358
+ "normalized": false,
359
+ "rstrip": false,
360
+ "single_word": false,
361
+ "special": true
362
+ },
363
+ "128045": {
364
+ "content": "<|reserved_special_token_37|>",
365
+ "lstrip": false,
366
+ "normalized": false,
367
+ "rstrip": false,
368
+ "single_word": false,
369
+ "special": true
370
+ },
371
+ "128046": {
372
+ "content": "<|reserved_special_token_38|>",
373
+ "lstrip": false,
374
+ "normalized": false,
375
+ "rstrip": false,
376
+ "single_word": false,
377
+ "special": true
378
+ },
379
+ "128047": {
380
+ "content": "<|reserved_special_token_39|>",
381
+ "lstrip": false,
382
+ "normalized": false,
383
+ "rstrip": false,
384
+ "single_word": false,
385
+ "special": true
386
+ },
387
+ "128048": {
388
+ "content": "<|reserved_special_token_40|>",
389
+ "lstrip": false,
390
+ "normalized": false,
391
+ "rstrip": false,
392
+ "single_word": false,
393
+ "special": true
394
+ },
395
+ "128049": {
396
+ "content": "<|reserved_special_token_41|>",
397
+ "lstrip": false,
398
+ "normalized": false,
399
+ "rstrip": false,
400
+ "single_word": false,
401
+ "special": true
402
+ },
403
+ "128050": {
404
+ "content": "<|reserved_special_token_42|>",
405
+ "lstrip": false,
406
+ "normalized": false,
407
+ "rstrip": false,
408
+ "single_word": false,
409
+ "special": true
410
+ },
411
+ "128051": {
412
+ "content": "<|reserved_special_token_43|>",
413
+ "lstrip": false,
414
+ "normalized": false,
415
+ "rstrip": false,
416
+ "single_word": false,
417
+ "special": true
418
+ },
419
+ "128052": {
420
+ "content": "<|reserved_special_token_44|>",
421
+ "lstrip": false,
422
+ "normalized": false,
423
+ "rstrip": false,
424
+ "single_word": false,
425
+ "special": true
426
+ },
427
+ "128053": {
428
+ "content": "<|reserved_special_token_45|>",
429
+ "lstrip": false,
430
+ "normalized": false,
431
+ "rstrip": false,
432
+ "single_word": false,
433
+ "special": true
434
+ },
435
+ "128054": {
436
+ "content": "<|reserved_special_token_46|>",
437
+ "lstrip": false,
438
+ "normalized": false,
439
+ "rstrip": false,
440
+ "single_word": false,
441
+ "special": true
442
+ },
443
+ "128055": {
444
+ "content": "<|reserved_special_token_47|>",
445
+ "lstrip": false,
446
+ "normalized": false,
447
+ "rstrip": false,
448
+ "single_word": false,
449
+ "special": true
450
+ },
451
+ "128056": {
452
+ "content": "<|reserved_special_token_48|>",
453
+ "lstrip": false,
454
+ "normalized": false,
455
+ "rstrip": false,
456
+ "single_word": false,
457
+ "special": true
458
+ },
459
+ "128057": {
460
+ "content": "<|reserved_special_token_49|>",
461
+ "lstrip": false,
462
+ "normalized": false,
463
+ "rstrip": false,
464
+ "single_word": false,
465
+ "special": true
466
+ },
467
+ "128058": {
468
+ "content": "<|reserved_special_token_50|>",
469
+ "lstrip": false,
470
+ "normalized": false,
471
+ "rstrip": false,
472
+ "single_word": false,
473
+ "special": true
474
+ },
475
+ "128059": {
476
+ "content": "<|reserved_special_token_51|>",
477
+ "lstrip": false,
478
+ "normalized": false,
479
+ "rstrip": false,
480
+ "single_word": false,
481
+ "special": true
482
+ },
483
+ "128060": {
484
+ "content": "<|reserved_special_token_52|>",
485
+ "lstrip": false,
486
+ "normalized": false,
487
+ "rstrip": false,
488
+ "single_word": false,
489
+ "special": true
490
+ },
491
+ "128061": {
492
+ "content": "<|reserved_special_token_53|>",
493
+ "lstrip": false,
494
+ "normalized": false,
495
+ "rstrip": false,
496
+ "single_word": false,
497
+ "special": true
498
+ },
499
+ "128062": {
500
+ "content": "<|reserved_special_token_54|>",
501
+ "lstrip": false,
502
+ "normalized": false,
503
+ "rstrip": false,
504
+ "single_word": false,
505
+ "special": true
506
+ },
507
+ "128063": {
508
+ "content": "<|reserved_special_token_55|>",
509
+ "lstrip": false,
510
+ "normalized": false,
511
+ "rstrip": false,
512
+ "single_word": false,
513
+ "special": true
514
+ },
515
+ "128064": {
516
+ "content": "<|reserved_special_token_56|>",
517
+ "lstrip": false,
518
+ "normalized": false,
519
+ "rstrip": false,
520
+ "single_word": false,
521
+ "special": true
522
+ },
523
+ "128065": {
524
+ "content": "<|reserved_special_token_57|>",
525
+ "lstrip": false,
526
+ "normalized": false,
527
+ "rstrip": false,
528
+ "single_word": false,
529
+ "special": true
530
+ },
531
+ "128066": {
532
+ "content": "<|reserved_special_token_58|>",
533
+ "lstrip": false,
534
+ "normalized": false,
535
+ "rstrip": false,
536
+ "single_word": false,
537
+ "special": true
538
+ },
539
+ "128067": {
540
+ "content": "<|reserved_special_token_59|>",
541
+ "lstrip": false,
542
+ "normalized": false,
543
+ "rstrip": false,
544
+ "single_word": false,
545
+ "special": true
546
+ },
547
+ "128068": {
548
+ "content": "<|reserved_special_token_60|>",
549
+ "lstrip": false,
550
+ "normalized": false,
551
+ "rstrip": false,
552
+ "single_word": false,
553
+ "special": true
554
+ },
555
+ "128069": {
556
+ "content": "<|reserved_special_token_61|>",
557
+ "lstrip": false,
558
+ "normalized": false,
559
+ "rstrip": false,
560
+ "single_word": false,
561
+ "special": true
562
+ },
563
+ "128070": {
564
+ "content": "<|reserved_special_token_62|>",
565
+ "lstrip": false,
566
+ "normalized": false,
567
+ "rstrip": false,
568
+ "single_word": false,
569
+ "special": true
570
+ },
571
+ "128071": {
572
+ "content": "<|reserved_special_token_63|>",
573
+ "lstrip": false,
574
+ "normalized": false,
575
+ "rstrip": false,
576
+ "single_word": false,
577
+ "special": true
578
+ },
579
+ "128072": {
580
+ "content": "<|reserved_special_token_64|>",
581
+ "lstrip": false,
582
+ "normalized": false,
583
+ "rstrip": false,
584
+ "single_word": false,
585
+ "special": true
586
+ },
587
+ "128073": {
588
+ "content": "<|reserved_special_token_65|>",
589
+ "lstrip": false,
590
+ "normalized": false,
591
+ "rstrip": false,
592
+ "single_word": false,
593
+ "special": true
594
+ },
595
+ "128074": {
596
+ "content": "<|reserved_special_token_66|>",
597
+ "lstrip": false,
598
+ "normalized": false,
599
+ "rstrip": false,
600
+ "single_word": false,
601
+ "special": true
602
+ },
603
+ "128075": {
604
+ "content": "<|reserved_special_token_67|>",
605
+ "lstrip": false,
606
+ "normalized": false,
607
+ "rstrip": false,
608
+ "single_word": false,
609
+ "special": true
610
+ },
611
+ "128076": {
612
+ "content": "<|reserved_special_token_68|>",
613
+ "lstrip": false,
614
+ "normalized": false,
615
+ "rstrip": false,
616
+ "single_word": false,
617
+ "special": true
618
+ },
619
+ "128077": {
620
+ "content": "<|reserved_special_token_69|>",
621
+ "lstrip": false,
622
+ "normalized": false,
623
+ "rstrip": false,
624
+ "single_word": false,
625
+ "special": true
626
+ },
627
+ "128078": {
628
+ "content": "<|reserved_special_token_70|>",
629
+ "lstrip": false,
630
+ "normalized": false,
631
+ "rstrip": false,
632
+ "single_word": false,
633
+ "special": true
634
+ },
635
+ "128079": {
636
+ "content": "<|reserved_special_token_71|>",
637
+ "lstrip": false,
638
+ "normalized": false,
639
+ "rstrip": false,
640
+ "single_word": false,
641
+ "special": true
642
+ },
643
+ "128080": {
644
+ "content": "<|reserved_special_token_72|>",
645
+ "lstrip": false,
646
+ "normalized": false,
647
+ "rstrip": false,
648
+ "single_word": false,
649
+ "special": true
650
+ },
651
+ "128081": {
652
+ "content": "<|reserved_special_token_73|>",
653
+ "lstrip": false,
654
+ "normalized": false,
655
+ "rstrip": false,
656
+ "single_word": false,
657
+ "special": true
658
+ },
659
+ "128082": {
660
+ "content": "<|reserved_special_token_74|>",
661
+ "lstrip": false,
662
+ "normalized": false,
663
+ "rstrip": false,
664
+ "single_word": false,
665
+ "special": true
666
+ },
667
+ "128083": {
668
+ "content": "<|reserved_special_token_75|>",
669
+ "lstrip": false,
670
+ "normalized": false,
671
+ "rstrip": false,
672
+ "single_word": false,
673
+ "special": true
674
+ },
675
+ "128084": {
676
+ "content": "<|reserved_special_token_76|>",
677
+ "lstrip": false,
678
+ "normalized": false,
679
+ "rstrip": false,
680
+ "single_word": false,
681
+ "special": true
682
+ },
683
+ "128085": {
684
+ "content": "<|reserved_special_token_77|>",
685
+ "lstrip": false,
686
+ "normalized": false,
687
+ "rstrip": false,
688
+ "single_word": false,
689
+ "special": true
690
+ },
691
+ "128086": {
692
+ "content": "<|reserved_special_token_78|>",
693
+ "lstrip": false,
694
+ "normalized": false,
695
+ "rstrip": false,
696
+ "single_word": false,
697
+ "special": true
698
+ },
699
+ "128087": {
700
+ "content": "<|reserved_special_token_79|>",
701
+ "lstrip": false,
702
+ "normalized": false,
703
+ "rstrip": false,
704
+ "single_word": false,
705
+ "special": true
706
+ },
707
+ "128088": {
708
+ "content": "<|reserved_special_token_80|>",
709
+ "lstrip": false,
710
+ "normalized": false,
711
+ "rstrip": false,
712
+ "single_word": false,
713
+ "special": true
714
+ },
715
+ "128089": {
716
+ "content": "<|reserved_special_token_81|>",
717
+ "lstrip": false,
718
+ "normalized": false,
719
+ "rstrip": false,
720
+ "single_word": false,
721
+ "special": true
722
+ },
723
+ "128090": {
724
+ "content": "<|reserved_special_token_82|>",
725
+ "lstrip": false,
726
+ "normalized": false,
727
+ "rstrip": false,
728
+ "single_word": false,
729
+ "special": true
730
+ },
731
+ "128091": {
732
+ "content": "<|reserved_special_token_83|>",
733
+ "lstrip": false,
734
+ "normalized": false,
735
+ "rstrip": false,
736
+ "single_word": false,
737
+ "special": true
738
+ },
739
+ "128092": {
740
+ "content": "<|reserved_special_token_84|>",
741
+ "lstrip": false,
742
+ "normalized": false,
743
+ "rstrip": false,
744
+ "single_word": false,
745
+ "special": true
746
+ },
747
+ "128093": {
748
+ "content": "<|reserved_special_token_85|>",
749
+ "lstrip": false,
750
+ "normalized": false,
751
+ "rstrip": false,
752
+ "single_word": false,
753
+ "special": true
754
+ },
755
+ "128094": {
756
+ "content": "<|reserved_special_token_86|>",
757
+ "lstrip": false,
758
+ "normalized": false,
759
+ "rstrip": false,
760
+ "single_word": false,
761
+ "special": true
762
+ },
763
+ "128095": {
764
+ "content": "<|reserved_special_token_87|>",
765
+ "lstrip": false,
766
+ "normalized": false,
767
+ "rstrip": false,
768
+ "single_word": false,
769
+ "special": true
770
+ },
771
+ "128096": {
772
+ "content": "<|reserved_special_token_88|>",
773
+ "lstrip": false,
774
+ "normalized": false,
775
+ "rstrip": false,
776
+ "single_word": false,
777
+ "special": true
778
+ },
779
+ "128097": {
780
+ "content": "<|reserved_special_token_89|>",
781
+ "lstrip": false,
782
+ "normalized": false,
783
+ "rstrip": false,
784
+ "single_word": false,
785
+ "special": true
786
+ },
787
+ "128098": {
788
+ "content": "<|reserved_special_token_90|>",
789
+ "lstrip": false,
790
+ "normalized": false,
791
+ "rstrip": false,
792
+ "single_word": false,
793
+ "special": true
794
+ },
795
+ "128099": {
796
+ "content": "<|reserved_special_token_91|>",
797
+ "lstrip": false,
798
+ "normalized": false,
799
+ "rstrip": false,
800
+ "single_word": false,
801
+ "special": true
802
+ },
803
+ "128100": {
804
+ "content": "<|reserved_special_token_92|>",
805
+ "lstrip": false,
806
+ "normalized": false,
807
+ "rstrip": false,
808
+ "single_word": false,
809
+ "special": true
810
+ },
811
+ "128101": {
812
+ "content": "<|reserved_special_token_93|>",
813
+ "lstrip": false,
814
+ "normalized": false,
815
+ "rstrip": false,
816
+ "single_word": false,
817
+ "special": true
818
+ },
819
+ "128102": {
820
+ "content": "<|reserved_special_token_94|>",
821
+ "lstrip": false,
822
+ "normalized": false,
823
+ "rstrip": false,
824
+ "single_word": false,
825
+ "special": true
826
+ },
827
+ "128103": {
828
+ "content": "<|reserved_special_token_95|>",
829
+ "lstrip": false,
830
+ "normalized": false,
831
+ "rstrip": false,
832
+ "single_word": false,
833
+ "special": true
834
+ },
835
+ "128104": {
836
+ "content": "<|reserved_special_token_96|>",
837
+ "lstrip": false,
838
+ "normalized": false,
839
+ "rstrip": false,
840
+ "single_word": false,
841
+ "special": true
842
+ },
843
+ "128105": {
844
+ "content": "<|reserved_special_token_97|>",
845
+ "lstrip": false,
846
+ "normalized": false,
847
+ "rstrip": false,
848
+ "single_word": false,
849
+ "special": true
850
+ },
851
+ "128106": {
852
+ "content": "<|reserved_special_token_98|>",
853
+ "lstrip": false,
854
+ "normalized": false,
855
+ "rstrip": false,
856
+ "single_word": false,
857
+ "special": true
858
+ },
859
+ "128107": {
860
+ "content": "<|reserved_special_token_99|>",
861
+ "lstrip": false,
862
+ "normalized": false,
863
+ "rstrip": false,
864
+ "single_word": false,
865
+ "special": true
866
+ },
867
+ "128108": {
868
+ "content": "<|reserved_special_token_100|>",
869
+ "lstrip": false,
870
+ "normalized": false,
871
+ "rstrip": false,
872
+ "single_word": false,
873
+ "special": true
874
+ },
875
+ "128109": {
876
+ "content": "<|reserved_special_token_101|>",
877
+ "lstrip": false,
878
+ "normalized": false,
879
+ "rstrip": false,
880
+ "single_word": false,
881
+ "special": true
882
+ },
883
+ "128110": {
884
+ "content": "<|reserved_special_token_102|>",
885
+ "lstrip": false,
886
+ "normalized": false,
887
+ "rstrip": false,
888
+ "single_word": false,
889
+ "special": true
890
+ },
891
+ "128111": {
892
+ "content": "<|reserved_special_token_103|>",
893
+ "lstrip": false,
894
+ "normalized": false,
895
+ "rstrip": false,
896
+ "single_word": false,
897
+ "special": true
898
+ },
899
+ "128112": {
900
+ "content": "<|reserved_special_token_104|>",
901
+ "lstrip": false,
902
+ "normalized": false,
903
+ "rstrip": false,
904
+ "single_word": false,
905
+ "special": true
906
+ },
907
+ "128113": {
908
+ "content": "<|reserved_special_token_105|>",
909
+ "lstrip": false,
910
+ "normalized": false,
911
+ "rstrip": false,
912
+ "single_word": false,
913
+ "special": true
914
+ },
915
+ "128114": {
916
+ "content": "<|reserved_special_token_106|>",
917
+ "lstrip": false,
918
+ "normalized": false,
919
+ "rstrip": false,
920
+ "single_word": false,
921
+ "special": true
922
+ },
923
+ "128115": {
924
+ "content": "<|reserved_special_token_107|>",
925
+ "lstrip": false,
926
+ "normalized": false,
927
+ "rstrip": false,
928
+ "single_word": false,
929
+ "special": true
930
+ },
931
+ "128116": {
932
+ "content": "<|reserved_special_token_108|>",
933
+ "lstrip": false,
934
+ "normalized": false,
935
+ "rstrip": false,
936
+ "single_word": false,
937
+ "special": true
938
+ },
939
+ "128117": {
940
+ "content": "<|reserved_special_token_109|>",
941
+ "lstrip": false,
942
+ "normalized": false,
943
+ "rstrip": false,
944
+ "single_word": false,
945
+ "special": true
946
+ },
947
+ "128118": {
948
+ "content": "<|reserved_special_token_110|>",
949
+ "lstrip": false,
950
+ "normalized": false,
951
+ "rstrip": false,
952
+ "single_word": false,
953
+ "special": true
954
+ },
955
+ "128119": {
956
+ "content": "<|reserved_special_token_111|>",
957
+ "lstrip": false,
958
+ "normalized": false,
959
+ "rstrip": false,
960
+ "single_word": false,
961
+ "special": true
962
+ },
963
+ "128120": {
964
+ "content": "<|reserved_special_token_112|>",
965
+ "lstrip": false,
966
+ "normalized": false,
967
+ "rstrip": false,
968
+ "single_word": false,
969
+ "special": true
970
+ },
971
+ "128121": {
972
+ "content": "<|reserved_special_token_113|>",
973
+ "lstrip": false,
974
+ "normalized": false,
975
+ "rstrip": false,
976
+ "single_word": false,
977
+ "special": true
978
+ },
979
+ "128122": {
980
+ "content": "<|reserved_special_token_114|>",
981
+ "lstrip": false,
982
+ "normalized": false,
983
+ "rstrip": false,
984
+ "single_word": false,
985
+ "special": true
986
+ },
987
+ "128123": {
988
+ "content": "<|reserved_special_token_115|>",
989
+ "lstrip": false,
990
+ "normalized": false,
991
+ "rstrip": false,
992
+ "single_word": false,
993
+ "special": true
994
+ },
995
+ "128124": {
996
+ "content": "<|reserved_special_token_116|>",
997
+ "lstrip": false,
998
+ "normalized": false,
999
+ "rstrip": false,
1000
+ "single_word": false,
1001
+ "special": true
1002
+ },
1003
+ "128125": {
1004
+ "content": "<|reserved_special_token_117|>",
1005
+ "lstrip": false,
1006
+ "normalized": false,
1007
+ "rstrip": false,
1008
+ "single_word": false,
1009
+ "special": true
1010
+ },
1011
+ "128126": {
1012
+ "content": "<|reserved_special_token_118|>",
1013
+ "lstrip": false,
1014
+ "normalized": false,
1015
+ "rstrip": false,
1016
+ "single_word": false,
1017
+ "special": true
1018
+ },
1019
+ "128127": {
1020
+ "content": "<|reserved_special_token_119|>",
1021
+ "lstrip": false,
1022
+ "normalized": false,
1023
+ "rstrip": false,
1024
+ "single_word": false,
1025
+ "special": true
1026
+ },
1027
+ "128128": {
1028
+ "content": "<|reserved_special_token_120|>",
1029
+ "lstrip": false,
1030
+ "normalized": false,
1031
+ "rstrip": false,
1032
+ "single_word": false,
1033
+ "special": true
1034
+ },
1035
+ "128129": {
1036
+ "content": "<|reserved_special_token_121|>",
1037
+ "lstrip": false,
1038
+ "normalized": false,
1039
+ "rstrip": false,
1040
+ "single_word": false,
1041
+ "special": true
1042
+ },
1043
+ "128130": {
1044
+ "content": "<|reserved_special_token_122|>",
1045
+ "lstrip": false,
1046
+ "normalized": false,
1047
+ "rstrip": false,
1048
+ "single_word": false,
1049
+ "special": true
1050
+ },
1051
+ "128131": {
1052
+ "content": "<|reserved_special_token_123|>",
1053
+ "lstrip": false,
1054
+ "normalized": false,
1055
+ "rstrip": false,
1056
+ "single_word": false,
1057
+ "special": true
1058
+ },
1059
+ "128132": {
1060
+ "content": "<|reserved_special_token_124|>",
1061
+ "lstrip": false,
1062
+ "normalized": false,
1063
+ "rstrip": false,
1064
+ "single_word": false,
1065
+ "special": true
1066
+ },
1067
+ "128133": {
1068
+ "content": "<|reserved_special_token_125|>",
1069
+ "lstrip": false,
1070
+ "normalized": false,
1071
+ "rstrip": false,
1072
+ "single_word": false,
1073
+ "special": true
1074
+ },
1075
+ "128134": {
1076
+ "content": "<|reserved_special_token_126|>",
1077
+ "lstrip": false,
1078
+ "normalized": false,
1079
+ "rstrip": false,
1080
+ "single_word": false,
1081
+ "special": true
1082
+ },
1083
+ "128135": {
1084
+ "content": "<|reserved_special_token_127|>",
1085
+ "lstrip": false,
1086
+ "normalized": false,
1087
+ "rstrip": false,
1088
+ "single_word": false,
1089
+ "special": true
1090
+ },
1091
+ "128136": {
1092
+ "content": "<|reserved_special_token_128|>",
1093
+ "lstrip": false,
1094
+ "normalized": false,
1095
+ "rstrip": false,
1096
+ "single_word": false,
1097
+ "special": true
1098
+ },
1099
+ "128137": {
1100
+ "content": "<|reserved_special_token_129|>",
1101
+ "lstrip": false,
1102
+ "normalized": false,
1103
+ "rstrip": false,
1104
+ "single_word": false,
1105
+ "special": true
1106
+ },
1107
+ "128138": {
1108
+ "content": "<|reserved_special_token_130|>",
1109
+ "lstrip": false,
1110
+ "normalized": false,
1111
+ "rstrip": false,
1112
+ "single_word": false,
1113
+ "special": true
1114
+ },
1115
+ "128139": {
1116
+ "content": "<|reserved_special_token_131|>",
1117
+ "lstrip": false,
1118
+ "normalized": false,
1119
+ "rstrip": false,
1120
+ "single_word": false,
1121
+ "special": true
1122
+ },
1123
+ "128140": {
1124
+ "content": "<|reserved_special_token_132|>",
1125
+ "lstrip": false,
1126
+ "normalized": false,
1127
+ "rstrip": false,
1128
+ "single_word": false,
1129
+ "special": true
1130
+ },
1131
+ "128141": {
1132
+ "content": "<|reserved_special_token_133|>",
1133
+ "lstrip": false,
1134
+ "normalized": false,
1135
+ "rstrip": false,
1136
+ "single_word": false,
1137
+ "special": true
1138
+ },
1139
+ "128142": {
1140
+ "content": "<|reserved_special_token_134|>",
1141
+ "lstrip": false,
1142
+ "normalized": false,
1143
+ "rstrip": false,
1144
+ "single_word": false,
1145
+ "special": true
1146
+ },
1147
+ "128143": {
1148
+ "content": "<|reserved_special_token_135|>",
1149
+ "lstrip": false,
1150
+ "normalized": false,
1151
+ "rstrip": false,
1152
+ "single_word": false,
1153
+ "special": true
1154
+ },
1155
+ "128144": {
1156
+ "content": "<|reserved_special_token_136|>",
1157
+ "lstrip": false,
1158
+ "normalized": false,
1159
+ "rstrip": false,
1160
+ "single_word": false,
1161
+ "special": true
1162
+ },
1163
+ "128145": {
1164
+ "content": "<|reserved_special_token_137|>",
1165
+ "lstrip": false,
1166
+ "normalized": false,
1167
+ "rstrip": false,
1168
+ "single_word": false,
1169
+ "special": true
1170
+ },
1171
+ "128146": {
1172
+ "content": "<|reserved_special_token_138|>",
1173
+ "lstrip": false,
1174
+ "normalized": false,
1175
+ "rstrip": false,
1176
+ "single_word": false,
1177
+ "special": true
1178
+ },
1179
+ "128147": {
1180
+ "content": "<|reserved_special_token_139|>",
1181
+ "lstrip": false,
1182
+ "normalized": false,
1183
+ "rstrip": false,
1184
+ "single_word": false,
1185
+ "special": true
1186
+ },
1187
+ "128148": {
1188
+ "content": "<|reserved_special_token_140|>",
1189
+ "lstrip": false,
1190
+ "normalized": false,
1191
+ "rstrip": false,
1192
+ "single_word": false,
1193
+ "special": true
1194
+ },
1195
+ "128149": {
1196
+ "content": "<|reserved_special_token_141|>",
1197
+ "lstrip": false,
1198
+ "normalized": false,
1199
+ "rstrip": false,
1200
+ "single_word": false,
1201
+ "special": true
1202
+ },
1203
+ "128150": {
1204
+ "content": "<|reserved_special_token_142|>",
1205
+ "lstrip": false,
1206
+ "normalized": false,
1207
+ "rstrip": false,
1208
+ "single_word": false,
1209
+ "special": true
1210
+ },
1211
+ "128151": {
1212
+ "content": "<|reserved_special_token_143|>",
1213
+ "lstrip": false,
1214
+ "normalized": false,
1215
+ "rstrip": false,
1216
+ "single_word": false,
1217
+ "special": true
1218
+ },
1219
+ "128152": {
1220
+ "content": "<|reserved_special_token_144|>",
1221
+ "lstrip": false,
1222
+ "normalized": false,
1223
+ "rstrip": false,
1224
+ "single_word": false,
1225
+ "special": true
1226
+ },
1227
+ "128153": {
1228
+ "content": "<|reserved_special_token_145|>",
1229
+ "lstrip": false,
1230
+ "normalized": false,
1231
+ "rstrip": false,
1232
+ "single_word": false,
1233
+ "special": true
1234
+ },
1235
+ "128154": {
1236
+ "content": "<|reserved_special_token_146|>",
1237
+ "lstrip": false,
1238
+ "normalized": false,
1239
+ "rstrip": false,
1240
+ "single_word": false,
1241
+ "special": true
1242
+ },
1243
+ "128155": {
1244
+ "content": "<|reserved_special_token_147|>",
1245
+ "lstrip": false,
1246
+ "normalized": false,
1247
+ "rstrip": false,
1248
+ "single_word": false,
1249
+ "special": true
1250
+ },
1251
+ "128156": {
1252
+ "content": "<|reserved_special_token_148|>",
1253
+ "lstrip": false,
1254
+ "normalized": false,
1255
+ "rstrip": false,
1256
+ "single_word": false,
1257
+ "special": true
1258
+ },
1259
+ "128157": {
1260
+ "content": "<|reserved_special_token_149|>",
1261
+ "lstrip": false,
1262
+ "normalized": false,
1263
+ "rstrip": false,
1264
+ "single_word": false,
1265
+ "special": true
1266
+ },
1267
+ "128158": {
1268
+ "content": "<|reserved_special_token_150|>",
1269
+ "lstrip": false,
1270
+ "normalized": false,
1271
+ "rstrip": false,
1272
+ "single_word": false,
1273
+ "special": true
1274
+ },
1275
+ "128159": {
1276
+ "content": "<|reserved_special_token_151|>",
1277
+ "lstrip": false,
1278
+ "normalized": false,
1279
+ "rstrip": false,
1280
+ "single_word": false,
1281
+ "special": true
1282
+ },
1283
+ "128160": {
1284
+ "content": "<|reserved_special_token_152|>",
1285
+ "lstrip": false,
1286
+ "normalized": false,
1287
+ "rstrip": false,
1288
+ "single_word": false,
1289
+ "special": true
1290
+ },
1291
+ "128161": {
1292
+ "content": "<|reserved_special_token_153|>",
1293
+ "lstrip": false,
1294
+ "normalized": false,
1295
+ "rstrip": false,
1296
+ "single_word": false,
1297
+ "special": true
1298
+ },
1299
+ "128162": {
1300
+ "content": "<|reserved_special_token_154|>",
1301
+ "lstrip": false,
1302
+ "normalized": false,
1303
+ "rstrip": false,
1304
+ "single_word": false,
1305
+ "special": true
1306
+ },
1307
+ "128163": {
1308
+ "content": "<|reserved_special_token_155|>",
1309
+ "lstrip": false,
1310
+ "normalized": false,
1311
+ "rstrip": false,
1312
+ "single_word": false,
1313
+ "special": true
1314
+ },
1315
+ "128164": {
1316
+ "content": "<|reserved_special_token_156|>",
1317
+ "lstrip": false,
1318
+ "normalized": false,
1319
+ "rstrip": false,
1320
+ "single_word": false,
1321
+ "special": true
1322
+ },
1323
+ "128165": {
1324
+ "content": "<|reserved_special_token_157|>",
1325
+ "lstrip": false,
1326
+ "normalized": false,
1327
+ "rstrip": false,
1328
+ "single_word": false,
1329
+ "special": true
1330
+ },
1331
+ "128166": {
1332
+ "content": "<|reserved_special_token_158|>",
1333
+ "lstrip": false,
1334
+ "normalized": false,
1335
+ "rstrip": false,
1336
+ "single_word": false,
1337
+ "special": true
1338
+ },
1339
+ "128167": {
1340
+ "content": "<|reserved_special_token_159|>",
1341
+ "lstrip": false,
1342
+ "normalized": false,
1343
+ "rstrip": false,
1344
+ "single_word": false,
1345
+ "special": true
1346
+ },
1347
+ "128168": {
1348
+ "content": "<|reserved_special_token_160|>",
1349
+ "lstrip": false,
1350
+ "normalized": false,
1351
+ "rstrip": false,
1352
+ "single_word": false,
1353
+ "special": true
1354
+ },
1355
+ "128169": {
1356
+ "content": "<|reserved_special_token_161|>",
1357
+ "lstrip": false,
1358
+ "normalized": false,
1359
+ "rstrip": false,
1360
+ "single_word": false,
1361
+ "special": true
1362
+ },
1363
+ "128170": {
1364
+ "content": "<|reserved_special_token_162|>",
1365
+ "lstrip": false,
1366
+ "normalized": false,
1367
+ "rstrip": false,
1368
+ "single_word": false,
1369
+ "special": true
1370
+ },
1371
+ "128171": {
1372
+ "content": "<|reserved_special_token_163|>",
1373
+ "lstrip": false,
1374
+ "normalized": false,
1375
+ "rstrip": false,
1376
+ "single_word": false,
1377
+ "special": true
1378
+ },
1379
+ "128172": {
1380
+ "content": "<|reserved_special_token_164|>",
1381
+ "lstrip": false,
1382
+ "normalized": false,
1383
+ "rstrip": false,
1384
+ "single_word": false,
1385
+ "special": true
1386
+ },
1387
+ "128173": {
1388
+ "content": "<|reserved_special_token_165|>",
1389
+ "lstrip": false,
1390
+ "normalized": false,
1391
+ "rstrip": false,
1392
+ "single_word": false,
1393
+ "special": true
1394
+ },
1395
+ "128174": {
1396
+ "content": "<|reserved_special_token_166|>",
1397
+ "lstrip": false,
1398
+ "normalized": false,
1399
+ "rstrip": false,
1400
+ "single_word": false,
1401
+ "special": true
1402
+ },
1403
+ "128175": {
1404
+ "content": "<|reserved_special_token_167|>",
1405
+ "lstrip": false,
1406
+ "normalized": false,
1407
+ "rstrip": false,
1408
+ "single_word": false,
1409
+ "special": true
1410
+ },
1411
+ "128176": {
1412
+ "content": "<|reserved_special_token_168|>",
1413
+ "lstrip": false,
1414
+ "normalized": false,
1415
+ "rstrip": false,
1416
+ "single_word": false,
1417
+ "special": true
1418
+ },
1419
+ "128177": {
1420
+ "content": "<|reserved_special_token_169|>",
1421
+ "lstrip": false,
1422
+ "normalized": false,
1423
+ "rstrip": false,
1424
+ "single_word": false,
1425
+ "special": true
1426
+ },
1427
+ "128178": {
1428
+ "content": "<|reserved_special_token_170|>",
1429
+ "lstrip": false,
1430
+ "normalized": false,
1431
+ "rstrip": false,
1432
+ "single_word": false,
1433
+ "special": true
1434
+ },
1435
+ "128179": {
1436
+ "content": "<|reserved_special_token_171|>",
1437
+ "lstrip": false,
1438
+ "normalized": false,
1439
+ "rstrip": false,
1440
+ "single_word": false,
1441
+ "special": true
1442
+ },
1443
+ "128180": {
1444
+ "content": "<|reserved_special_token_172|>",
1445
+ "lstrip": false,
1446
+ "normalized": false,
1447
+ "rstrip": false,
1448
+ "single_word": false,
1449
+ "special": true
1450
+ },
1451
+ "128181": {
1452
+ "content": "<|reserved_special_token_173|>",
1453
+ "lstrip": false,
1454
+ "normalized": false,
1455
+ "rstrip": false,
1456
+ "single_word": false,
1457
+ "special": true
1458
+ },
1459
+ "128182": {
1460
+ "content": "<|reserved_special_token_174|>",
1461
+ "lstrip": false,
1462
+ "normalized": false,
1463
+ "rstrip": false,
1464
+ "single_word": false,
1465
+ "special": true
1466
+ },
1467
+ "128183": {
1468
+ "content": "<|reserved_special_token_175|>",
1469
+ "lstrip": false,
1470
+ "normalized": false,
1471
+ "rstrip": false,
1472
+ "single_word": false,
1473
+ "special": true
1474
+ },
1475
+ "128184": {
1476
+ "content": "<|reserved_special_token_176|>",
1477
+ "lstrip": false,
1478
+ "normalized": false,
1479
+ "rstrip": false,
1480
+ "single_word": false,
1481
+ "special": true
1482
+ },
1483
+ "128185": {
1484
+ "content": "<|reserved_special_token_177|>",
1485
+ "lstrip": false,
1486
+ "normalized": false,
1487
+ "rstrip": false,
1488
+ "single_word": false,
1489
+ "special": true
1490
+ },
1491
+ "128186": {
1492
+ "content": "<|reserved_special_token_178|>",
1493
+ "lstrip": false,
1494
+ "normalized": false,
1495
+ "rstrip": false,
1496
+ "single_word": false,
1497
+ "special": true
1498
+ },
1499
+ "128187": {
1500
+ "content": "<|reserved_special_token_179|>",
1501
+ "lstrip": false,
1502
+ "normalized": false,
1503
+ "rstrip": false,
1504
+ "single_word": false,
1505
+ "special": true
1506
+ },
1507
+ "128188": {
1508
+ "content": "<|reserved_special_token_180|>",
1509
+ "lstrip": false,
1510
+ "normalized": false,
1511
+ "rstrip": false,
1512
+ "single_word": false,
1513
+ "special": true
1514
+ },
1515
+ "128189": {
1516
+ "content": "<|reserved_special_token_181|>",
1517
+ "lstrip": false,
1518
+ "normalized": false,
1519
+ "rstrip": false,
1520
+ "single_word": false,
1521
+ "special": true
1522
+ },
1523
+ "128190": {
1524
+ "content": "<|reserved_special_token_182|>",
1525
+ "lstrip": false,
1526
+ "normalized": false,
1527
+ "rstrip": false,
1528
+ "single_word": false,
1529
+ "special": true
1530
+ },
1531
+ "128191": {
1532
+ "content": "<|reserved_special_token_183|>",
1533
+ "lstrip": false,
1534
+ "normalized": false,
1535
+ "rstrip": false,
1536
+ "single_word": false,
1537
+ "special": true
1538
+ },
1539
+ "128192": {
1540
+ "content": "<|reserved_special_token_184|>",
1541
+ "lstrip": false,
1542
+ "normalized": false,
1543
+ "rstrip": false,
1544
+ "single_word": false,
1545
+ "special": true
1546
+ },
1547
+ "128193": {
1548
+ "content": "<|reserved_special_token_185|>",
1549
+ "lstrip": false,
1550
+ "normalized": false,
1551
+ "rstrip": false,
1552
+ "single_word": false,
1553
+ "special": true
1554
+ },
1555
+ "128194": {
1556
+ "content": "<|reserved_special_token_186|>",
1557
+ "lstrip": false,
1558
+ "normalized": false,
1559
+ "rstrip": false,
1560
+ "single_word": false,
1561
+ "special": true
1562
+ },
1563
+ "128195": {
1564
+ "content": "<|reserved_special_token_187|>",
1565
+ "lstrip": false,
1566
+ "normalized": false,
1567
+ "rstrip": false,
1568
+ "single_word": false,
1569
+ "special": true
1570
+ },
1571
+ "128196": {
1572
+ "content": "<|reserved_special_token_188|>",
1573
+ "lstrip": false,
1574
+ "normalized": false,
1575
+ "rstrip": false,
1576
+ "single_word": false,
1577
+ "special": true
1578
+ },
1579
+ "128197": {
1580
+ "content": "<|reserved_special_token_189|>",
1581
+ "lstrip": false,
1582
+ "normalized": false,
1583
+ "rstrip": false,
1584
+ "single_word": false,
1585
+ "special": true
1586
+ },
1587
+ "128198": {
1588
+ "content": "<|reserved_special_token_190|>",
1589
+ "lstrip": false,
1590
+ "normalized": false,
1591
+ "rstrip": false,
1592
+ "single_word": false,
1593
+ "special": true
1594
+ },
1595
+ "128199": {
1596
+ "content": "<|reserved_special_token_191|>",
1597
+ "lstrip": false,
1598
+ "normalized": false,
1599
+ "rstrip": false,
1600
+ "single_word": false,
1601
+ "special": true
1602
+ },
1603
+ "128200": {
1604
+ "content": "<|reserved_special_token_192|>",
1605
+ "lstrip": false,
1606
+ "normalized": false,
1607
+ "rstrip": false,
1608
+ "single_word": false,
1609
+ "special": true
1610
+ },
1611
+ "128201": {
1612
+ "content": "<|reserved_special_token_193|>",
1613
+ "lstrip": false,
1614
+ "normalized": false,
1615
+ "rstrip": false,
1616
+ "single_word": false,
1617
+ "special": true
1618
+ },
1619
+ "128202": {
1620
+ "content": "<|reserved_special_token_194|>",
1621
+ "lstrip": false,
1622
+ "normalized": false,
1623
+ "rstrip": false,
1624
+ "single_word": false,
1625
+ "special": true
1626
+ },
1627
+ "128203": {
1628
+ "content": "<|reserved_special_token_195|>",
1629
+ "lstrip": false,
1630
+ "normalized": false,
1631
+ "rstrip": false,
1632
+ "single_word": false,
1633
+ "special": true
1634
+ },
1635
+ "128204": {
1636
+ "content": "<|reserved_special_token_196|>",
1637
+ "lstrip": false,
1638
+ "normalized": false,
1639
+ "rstrip": false,
1640
+ "single_word": false,
1641
+ "special": true
1642
+ },
1643
+ "128205": {
1644
+ "content": "<|reserved_special_token_197|>",
1645
+ "lstrip": false,
1646
+ "normalized": false,
1647
+ "rstrip": false,
1648
+ "single_word": false,
1649
+ "special": true
1650
+ },
1651
+ "128206": {
1652
+ "content": "<|reserved_special_token_198|>",
1653
+ "lstrip": false,
1654
+ "normalized": false,
1655
+ "rstrip": false,
1656
+ "single_word": false,
1657
+ "special": true
1658
+ },
1659
+ "128207": {
1660
+ "content": "<|reserved_special_token_199|>",
1661
+ "lstrip": false,
1662
+ "normalized": false,
1663
+ "rstrip": false,
1664
+ "single_word": false,
1665
+ "special": true
1666
+ },
1667
+ "128208": {
1668
+ "content": "<|reserved_special_token_200|>",
1669
+ "lstrip": false,
1670
+ "normalized": false,
1671
+ "rstrip": false,
1672
+ "single_word": false,
1673
+ "special": true
1674
+ },
1675
+ "128209": {
1676
+ "content": "<|reserved_special_token_201|>",
1677
+ "lstrip": false,
1678
+ "normalized": false,
1679
+ "rstrip": false,
1680
+ "single_word": false,
1681
+ "special": true
1682
+ },
1683
+ "128210": {
1684
+ "content": "<|reserved_special_token_202|>",
1685
+ "lstrip": false,
1686
+ "normalized": false,
1687
+ "rstrip": false,
1688
+ "single_word": false,
1689
+ "special": true
1690
+ },
1691
+ "128211": {
1692
+ "content": "<|reserved_special_token_203|>",
1693
+ "lstrip": false,
1694
+ "normalized": false,
1695
+ "rstrip": false,
1696
+ "single_word": false,
1697
+ "special": true
1698
+ },
1699
+ "128212": {
1700
+ "content": "<|reserved_special_token_204|>",
1701
+ "lstrip": false,
1702
+ "normalized": false,
1703
+ "rstrip": false,
1704
+ "single_word": false,
1705
+ "special": true
1706
+ },
1707
+ "128213": {
1708
+ "content": "<|reserved_special_token_205|>",
1709
+ "lstrip": false,
1710
+ "normalized": false,
1711
+ "rstrip": false,
1712
+ "single_word": false,
1713
+ "special": true
1714
+ },
1715
+ "128214": {
1716
+ "content": "<|reserved_special_token_206|>",
1717
+ "lstrip": false,
1718
+ "normalized": false,
1719
+ "rstrip": false,
1720
+ "single_word": false,
1721
+ "special": true
1722
+ },
1723
+ "128215": {
1724
+ "content": "<|reserved_special_token_207|>",
1725
+ "lstrip": false,
1726
+ "normalized": false,
1727
+ "rstrip": false,
1728
+ "single_word": false,
1729
+ "special": true
1730
+ },
1731
+ "128216": {
1732
+ "content": "<|reserved_special_token_208|>",
1733
+ "lstrip": false,
1734
+ "normalized": false,
1735
+ "rstrip": false,
1736
+ "single_word": false,
1737
+ "special": true
1738
+ },
1739
+ "128217": {
1740
+ "content": "<|reserved_special_token_209|>",
1741
+ "lstrip": false,
1742
+ "normalized": false,
1743
+ "rstrip": false,
1744
+ "single_word": false,
1745
+ "special": true
1746
+ },
1747
+ "128218": {
1748
+ "content": "<|reserved_special_token_210|>",
1749
+ "lstrip": false,
1750
+ "normalized": false,
1751
+ "rstrip": false,
1752
+ "single_word": false,
1753
+ "special": true
1754
+ },
1755
+ "128219": {
1756
+ "content": "<|reserved_special_token_211|>",
1757
+ "lstrip": false,
1758
+ "normalized": false,
1759
+ "rstrip": false,
1760
+ "single_word": false,
1761
+ "special": true
1762
+ },
1763
+ "128220": {
1764
+ "content": "<|reserved_special_token_212|>",
1765
+ "lstrip": false,
1766
+ "normalized": false,
1767
+ "rstrip": false,
1768
+ "single_word": false,
1769
+ "special": true
1770
+ },
1771
+ "128221": {
1772
+ "content": "<|reserved_special_token_213|>",
1773
+ "lstrip": false,
1774
+ "normalized": false,
1775
+ "rstrip": false,
1776
+ "single_word": false,
1777
+ "special": true
1778
+ },
1779
+ "128222": {
1780
+ "content": "<|reserved_special_token_214|>",
1781
+ "lstrip": false,
1782
+ "normalized": false,
1783
+ "rstrip": false,
1784
+ "single_word": false,
1785
+ "special": true
1786
+ },
1787
+ "128223": {
1788
+ "content": "<|reserved_special_token_215|>",
1789
+ "lstrip": false,
1790
+ "normalized": false,
1791
+ "rstrip": false,
1792
+ "single_word": false,
1793
+ "special": true
1794
+ },
1795
+ "128224": {
1796
+ "content": "<|reserved_special_token_216|>",
1797
+ "lstrip": false,
1798
+ "normalized": false,
1799
+ "rstrip": false,
1800
+ "single_word": false,
1801
+ "special": true
1802
+ },
1803
+ "128225": {
1804
+ "content": "<|reserved_special_token_217|>",
1805
+ "lstrip": false,
1806
+ "normalized": false,
1807
+ "rstrip": false,
1808
+ "single_word": false,
1809
+ "special": true
1810
+ },
1811
+ "128226": {
1812
+ "content": "<|reserved_special_token_218|>",
1813
+ "lstrip": false,
1814
+ "normalized": false,
1815
+ "rstrip": false,
1816
+ "single_word": false,
1817
+ "special": true
1818
+ },
1819
+ "128227": {
1820
+ "content": "<|reserved_special_token_219|>",
1821
+ "lstrip": false,
1822
+ "normalized": false,
1823
+ "rstrip": false,
1824
+ "single_word": false,
1825
+ "special": true
1826
+ },
1827
+ "128228": {
1828
+ "content": "<|reserved_special_token_220|>",
1829
+ "lstrip": false,
1830
+ "normalized": false,
1831
+ "rstrip": false,
1832
+ "single_word": false,
1833
+ "special": true
1834
+ },
1835
+ "128229": {
1836
+ "content": "<|reserved_special_token_221|>",
1837
+ "lstrip": false,
1838
+ "normalized": false,
1839
+ "rstrip": false,
1840
+ "single_word": false,
1841
+ "special": true
1842
+ },
1843
+ "128230": {
1844
+ "content": "<|reserved_special_token_222|>",
1845
+ "lstrip": false,
1846
+ "normalized": false,
1847
+ "rstrip": false,
1848
+ "single_word": false,
1849
+ "special": true
1850
+ },
1851
+ "128231": {
1852
+ "content": "<|reserved_special_token_223|>",
1853
+ "lstrip": false,
1854
+ "normalized": false,
1855
+ "rstrip": false,
1856
+ "single_word": false,
1857
+ "special": true
1858
+ },
1859
+ "128232": {
1860
+ "content": "<|reserved_special_token_224|>",
1861
+ "lstrip": false,
1862
+ "normalized": false,
1863
+ "rstrip": false,
1864
+ "single_word": false,
1865
+ "special": true
1866
+ },
1867
+ "128233": {
1868
+ "content": "<|reserved_special_token_225|>",
1869
+ "lstrip": false,
1870
+ "normalized": false,
1871
+ "rstrip": false,
1872
+ "single_word": false,
1873
+ "special": true
1874
+ },
1875
+ "128234": {
1876
+ "content": "<|reserved_special_token_226|>",
1877
+ "lstrip": false,
1878
+ "normalized": false,
1879
+ "rstrip": false,
1880
+ "single_word": false,
1881
+ "special": true
1882
+ },
1883
+ "128235": {
1884
+ "content": "<|reserved_special_token_227|>",
1885
+ "lstrip": false,
1886
+ "normalized": false,
1887
+ "rstrip": false,
1888
+ "single_word": false,
1889
+ "special": true
1890
+ },
1891
+ "128236": {
1892
+ "content": "<|reserved_special_token_228|>",
1893
+ "lstrip": false,
1894
+ "normalized": false,
1895
+ "rstrip": false,
1896
+ "single_word": false,
1897
+ "special": true
1898
+ },
1899
+ "128237": {
1900
+ "content": "<|reserved_special_token_229|>",
1901
+ "lstrip": false,
1902
+ "normalized": false,
1903
+ "rstrip": false,
1904
+ "single_word": false,
1905
+ "special": true
1906
+ },
1907
+ "128238": {
1908
+ "content": "<|reserved_special_token_230|>",
1909
+ "lstrip": false,
1910
+ "normalized": false,
1911
+ "rstrip": false,
1912
+ "single_word": false,
1913
+ "special": true
1914
+ },
1915
+ "128239": {
1916
+ "content": "<|reserved_special_token_231|>",
1917
+ "lstrip": false,
1918
+ "normalized": false,
1919
+ "rstrip": false,
1920
+ "single_word": false,
1921
+ "special": true
1922
+ },
1923
+ "128240": {
1924
+ "content": "<|reserved_special_token_232|>",
1925
+ "lstrip": false,
1926
+ "normalized": false,
1927
+ "rstrip": false,
1928
+ "single_word": false,
1929
+ "special": true
1930
+ },
1931
+ "128241": {
1932
+ "content": "<|reserved_special_token_233|>",
1933
+ "lstrip": false,
1934
+ "normalized": false,
1935
+ "rstrip": false,
1936
+ "single_word": false,
1937
+ "special": true
1938
+ },
1939
+ "128242": {
1940
+ "content": "<|reserved_special_token_234|>",
1941
+ "lstrip": false,
1942
+ "normalized": false,
1943
+ "rstrip": false,
1944
+ "single_word": false,
1945
+ "special": true
1946
+ },
1947
+ "128243": {
1948
+ "content": "<|reserved_special_token_235|>",
1949
+ "lstrip": false,
1950
+ "normalized": false,
1951
+ "rstrip": false,
1952
+ "single_word": false,
1953
+ "special": true
1954
+ },
1955
+ "128244": {
1956
+ "content": "<|reserved_special_token_236|>",
1957
+ "lstrip": false,
1958
+ "normalized": false,
1959
+ "rstrip": false,
1960
+ "single_word": false,
1961
+ "special": true
1962
+ },
1963
+ "128245": {
1964
+ "content": "<|reserved_special_token_237|>",
1965
+ "lstrip": false,
1966
+ "normalized": false,
1967
+ "rstrip": false,
1968
+ "single_word": false,
1969
+ "special": true
1970
+ },
1971
+ "128246": {
1972
+ "content": "<|reserved_special_token_238|>",
1973
+ "lstrip": false,
1974
+ "normalized": false,
1975
+ "rstrip": false,
1976
+ "single_word": false,
1977
+ "special": true
1978
+ },
1979
+ "128247": {
1980
+ "content": "<|reserved_special_token_239|>",
1981
+ "lstrip": false,
1982
+ "normalized": false,
1983
+ "rstrip": false,
1984
+ "single_word": false,
1985
+ "special": true
1986
+ },
1987
+ "128248": {
1988
+ "content": "<|reserved_special_token_240|>",
1989
+ "lstrip": false,
1990
+ "normalized": false,
1991
+ "rstrip": false,
1992
+ "single_word": false,
1993
+ "special": true
1994
+ },
1995
+ "128249": {
1996
+ "content": "<|reserved_special_token_241|>",
1997
+ "lstrip": false,
1998
+ "normalized": false,
1999
+ "rstrip": false,
2000
+ "single_word": false,
2001
+ "special": true
2002
+ },
2003
+ "128250": {
2004
+ "content": "<|reserved_special_token_242|>",
2005
+ "lstrip": false,
2006
+ "normalized": false,
2007
+ "rstrip": false,
2008
+ "single_word": false,
2009
+ "special": true
2010
+ },
2011
+ "128251": {
2012
+ "content": "<|reserved_special_token_243|>",
2013
+ "lstrip": false,
2014
+ "normalized": false,
2015
+ "rstrip": false,
2016
+ "single_word": false,
2017
+ "special": true
2018
+ },
2019
+ "128252": {
2020
+ "content": "<|reserved_special_token_244|>",
2021
+ "lstrip": false,
2022
+ "normalized": false,
2023
+ "rstrip": false,
2024
+ "single_word": false,
2025
+ "special": true
2026
+ },
2027
+ "128253": {
2028
+ "content": "<|reserved_special_token_245|>",
2029
+ "lstrip": false,
2030
+ "normalized": false,
2031
+ "rstrip": false,
2032
+ "single_word": false,
2033
+ "special": true
2034
+ },
2035
+ "128254": {
2036
+ "content": "<|reserved_special_token_246|>",
2037
+ "lstrip": false,
2038
+ "normalized": false,
2039
+ "rstrip": false,
2040
+ "single_word": false,
2041
+ "special": true
2042
+ },
2043
+ "128255": {
2044
+ "content": "<|reserved_special_token_247|>",
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": "{{- bos_token }}\n{%- if custom_tools is defined %}\n {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n {%- set tools_in_user_message = true %}\n{%- endif %}\n{%- if not date_string is defined %}\n {%- set date_string = \"26 Jul 2024\" %}\n{%- endif %}\n{%- if not tools is defined %}\n {%- set tools = none %}\n{%- endif %}\n\n{#- This block extracts the system message, so we can slot it into the right place. #}\n{%- if messages[0]['role'] == 'system' %}\n {%- set system_message = messages[0]['content']|trim %}\n {%- set messages = messages[1:] %}\n{%- else %}\n {%- set system_message = \"\" %}\n{%- endif %}\n\n{#- System message + builtin tools #}\n{{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n{%- if builtin_tools is defined or tools is not none %}\n {{- \"Environment: ipython\\n\" }}\n{%- endif %}\n{%- if builtin_tools is defined %}\n {{- \"Tools: \" + builtin_tools | reject('equalto', 'code_interpreter') | join(\", \") + \"\\n\\n\"}}\n{%- endif %}\n{{- \"Cutting Knowledge Date: December 2023\\n\" }}\n{{- \"Today Date: \" + date_string + \"\\n\\n\" }}\n{%- if tools is not none and not tools_in_user_message %}\n {{- \"You have access to the following functions. To call a function, please respond with JSON for a function call.\" }}\n {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n {{- \"Do not use variables.\\n\\n\" }}\n {%- for t in tools %}\n {{- t | tojson(indent=4) }}\n {{- \"\\n\\n\" }}\n {%- endfor %}\n{%- endif %}\n{{- system_message }}\n{{- \"<|eot_id|>\" }}\n\n{#- Custom tools are passed in a user message with some extra guidance #}\n{%- if tools_in_user_message and not tools is none %}\n {#- Extract the first user message so we can plug it in here #}\n {%- if messages | length != 0 %}\n {%- set first_user_message = messages[0]['content']|trim %}\n {%- set messages = messages[1:] %}\n {%- else %}\n {{- raise_exception(\"Cannot put tools in the first user message when there's no first user message!\") }}\n{%- endif %}\n {{- '<|start_header_id|>user<|end_header_id|>\\n\\n' -}}\n {{- \"Given the following functions, please respond with a JSON for a function call \" }}\n {{- \"with its proper arguments that best answers the given prompt.\\n\\n\" }}\n {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n {{- \"Do not use variables.\\n\\n\" }}\n {%- for t in tools %}\n {{- t | tojson(indent=4) }}\n {{- \"\\n\\n\" }}\n {%- endfor %}\n {{- first_user_message + \"<|eot_id|>\"}}\n{%- endif %}\n\n{%- for message in messages %}\n {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}\n {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n'+ message['content'] | trim + '<|eot_id|>' }}\n {%- elif 'tool_calls' in message %}\n {%- if not message.tool_calls|length == 1 %}\n {{- raise_exception(\"This model only supports single tool-calls at once!\") }}\n {%- endif %}\n {%- set tool_call = message.tool_calls[0].function %}\n {%- if builtin_tools is defined and tool_call.name in builtin_tools %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n {{- \"<|python_tag|>\" + tool_call.name + \".call(\" }}\n {%- for arg_name, arg_val in tool_call.arguments | items %}\n {{- arg_name + '=\"' + arg_val + '\"' }}\n {%- if not loop.last %}\n {{- \", \" }}\n {%- endif %}\n {%- endfor %}\n {{- \")\" }}\n {%- else %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n {{- '\"parameters\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- \"}\" }}\n {%- endif %}\n {%- if builtin_tools is defined %}\n {#- This means we're in ipython mode #}\n {{- \"<|eom_id|>\" }}\n {%- else %}\n {{- \"<|eot_id|>\" }}\n {%- endif %}\n {%- elif message.role == \"tool\" or message.role == \"ipython\" %}\n {{- \"<|start_header_id|>ipython<|end_header_id|>\\n\\n\" }}\n {%- if message.content is mapping or message.content is iterable %}\n {{- message.content | tojson }}\n {%- else %}\n {{- message.content }}\n {%- endif %}\n {{- \"<|eot_id|>\" }}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}\n{%- endif %}\n",
2054
+ "clean_up_tokenization_spaces": true,
2055
+ "eos_token": "<|eot_id|>",
2056
+ "extra_special_tokens": {},
2057
+ "model_input_names": [
2058
+ "input_ids",
2059
+ "attention_mask"
2060
+ ],
2061
+ "model_max_length": 131072,
2062
+ "pad_token": "<|end_of_text|>",
2063
+ "tokenizer_class": "PreTrainedTokenizer"
2064
+ }
checkpoint-360/trainer_state.json ADDED
@@ -0,0 +1,2553 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": null,
3
+ "best_model_checkpoint": null,
4
+ "epoch": 5.0,
5
+ "eval_steps": 500,
6
+ "global_step": 360,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.013888888888888888,
13
+ "grad_norm": 95.33702850341797,
14
+ "learning_rate": 5.0000000000000004e-08,
15
+ "loss": 5.3695,
16
+ "step": 1
17
+ },
18
+ {
19
+ "epoch": 0.027777777777777776,
20
+ "grad_norm": 96.05199432373047,
21
+ "learning_rate": 1.0000000000000001e-07,
22
+ "loss": 5.4178,
23
+ "step": 2
24
+ },
25
+ {
26
+ "epoch": 0.041666666666666664,
27
+ "grad_norm": 92.71851348876953,
28
+ "learning_rate": 1.5000000000000002e-07,
29
+ "loss": 5.4472,
30
+ "step": 3
31
+ },
32
+ {
33
+ "epoch": 0.05555555555555555,
34
+ "grad_norm": 95.78789520263672,
35
+ "learning_rate": 2.0000000000000002e-07,
36
+ "loss": 5.4114,
37
+ "step": 4
38
+ },
39
+ {
40
+ "epoch": 0.06944444444444445,
41
+ "grad_norm": 95.62769317626953,
42
+ "learning_rate": 2.5000000000000004e-07,
43
+ "loss": 5.3612,
44
+ "step": 5
45
+ },
46
+ {
47
+ "epoch": 0.08333333333333333,
48
+ "grad_norm": 94.85267639160156,
49
+ "learning_rate": 3.0000000000000004e-07,
50
+ "loss": 5.4065,
51
+ "step": 6
52
+ },
53
+ {
54
+ "epoch": 0.09722222222222222,
55
+ "grad_norm": 93.81153869628906,
56
+ "learning_rate": 3.5000000000000004e-07,
57
+ "loss": 5.364,
58
+ "step": 7
59
+ },
60
+ {
61
+ "epoch": 0.1111111111111111,
62
+ "grad_norm": 95.33504486083984,
63
+ "learning_rate": 4.0000000000000003e-07,
64
+ "loss": 5.4484,
65
+ "step": 8
66
+ },
67
+ {
68
+ "epoch": 0.125,
69
+ "grad_norm": 94.11618041992188,
70
+ "learning_rate": 4.5000000000000003e-07,
71
+ "loss": 5.3494,
72
+ "step": 9
73
+ },
74
+ {
75
+ "epoch": 0.1388888888888889,
76
+ "grad_norm": 93.71621704101562,
77
+ "learning_rate": 5.000000000000001e-07,
78
+ "loss": 5.2325,
79
+ "step": 10
80
+ },
81
+ {
82
+ "epoch": 0.1527777777777778,
83
+ "grad_norm": 92.6498031616211,
84
+ "learning_rate": 5.5e-07,
85
+ "loss": 5.1224,
86
+ "step": 11
87
+ },
88
+ {
89
+ "epoch": 0.16666666666666666,
90
+ "grad_norm": 89.05821228027344,
91
+ "learning_rate": 6.000000000000001e-07,
92
+ "loss": 5.0484,
93
+ "step": 12
94
+ },
95
+ {
96
+ "epoch": 0.18055555555555555,
97
+ "grad_norm": 87.52056884765625,
98
+ "learning_rate": 6.5e-07,
99
+ "loss": 4.8831,
100
+ "step": 13
101
+ },
102
+ {
103
+ "epoch": 0.19444444444444445,
104
+ "grad_norm": 87.93170928955078,
105
+ "learning_rate": 7.000000000000001e-07,
106
+ "loss": 4.7723,
107
+ "step": 14
108
+ },
109
+ {
110
+ "epoch": 0.20833333333333334,
111
+ "grad_norm": 84.07933044433594,
112
+ "learning_rate": 7.5e-07,
113
+ "loss": 4.5843,
114
+ "step": 15
115
+ },
116
+ {
117
+ "epoch": 0.2222222222222222,
118
+ "grad_norm": 82.16165161132812,
119
+ "learning_rate": 8.000000000000001e-07,
120
+ "loss": 4.4273,
121
+ "step": 16
122
+ },
123
+ {
124
+ "epoch": 0.2361111111111111,
125
+ "grad_norm": 78.94780731201172,
126
+ "learning_rate": 8.500000000000001e-07,
127
+ "loss": 4.155,
128
+ "step": 17
129
+ },
130
+ {
131
+ "epoch": 0.25,
132
+ "grad_norm": 75.85335540771484,
133
+ "learning_rate": 9.000000000000001e-07,
134
+ "loss": 3.9005,
135
+ "step": 18
136
+ },
137
+ {
138
+ "epoch": 0.2638888888888889,
139
+ "grad_norm": 71.74459075927734,
140
+ "learning_rate": 9.500000000000001e-07,
141
+ "loss": 3.5885,
142
+ "step": 19
143
+ },
144
+ {
145
+ "epoch": 0.2777777777777778,
146
+ "grad_norm": 67.66385650634766,
147
+ "learning_rate": 1.0000000000000002e-06,
148
+ "loss": 3.308,
149
+ "step": 20
150
+ },
151
+ {
152
+ "epoch": 0.2916666666666667,
153
+ "grad_norm": 64.22036743164062,
154
+ "learning_rate": 1.0500000000000001e-06,
155
+ "loss": 3.057,
156
+ "step": 21
157
+ },
158
+ {
159
+ "epoch": 0.3055555555555556,
160
+ "grad_norm": 60.24971008300781,
161
+ "learning_rate": 1.1e-06,
162
+ "loss": 2.7939,
163
+ "step": 22
164
+ },
165
+ {
166
+ "epoch": 0.3194444444444444,
167
+ "grad_norm": 57.68950271606445,
168
+ "learning_rate": 1.1500000000000002e-06,
169
+ "loss": 2.5539,
170
+ "step": 23
171
+ },
172
+ {
173
+ "epoch": 0.3333333333333333,
174
+ "grad_norm": 56.10525894165039,
175
+ "learning_rate": 1.2000000000000002e-06,
176
+ "loss": 2.2688,
177
+ "step": 24
178
+ },
179
+ {
180
+ "epoch": 0.3472222222222222,
181
+ "grad_norm": 54.84128189086914,
182
+ "learning_rate": 1.25e-06,
183
+ "loss": 2.009,
184
+ "step": 25
185
+ },
186
+ {
187
+ "epoch": 0.3611111111111111,
188
+ "grad_norm": 53.96566390991211,
189
+ "learning_rate": 1.3e-06,
190
+ "loss": 1.6682,
191
+ "step": 26
192
+ },
193
+ {
194
+ "epoch": 0.375,
195
+ "grad_norm": 53.859439849853516,
196
+ "learning_rate": 1.3500000000000002e-06,
197
+ "loss": 1.3807,
198
+ "step": 27
199
+ },
200
+ {
201
+ "epoch": 0.3888888888888889,
202
+ "grad_norm": 53.22216796875,
203
+ "learning_rate": 1.4000000000000001e-06,
204
+ "loss": 1.1229,
205
+ "step": 28
206
+ },
207
+ {
208
+ "epoch": 0.4027777777777778,
209
+ "grad_norm": 50.3905143737793,
210
+ "learning_rate": 1.45e-06,
211
+ "loss": 0.8454,
212
+ "step": 29
213
+ },
214
+ {
215
+ "epoch": 0.4166666666666667,
216
+ "grad_norm": 40.14346694946289,
217
+ "learning_rate": 1.5e-06,
218
+ "loss": 0.5817,
219
+ "step": 30
220
+ },
221
+ {
222
+ "epoch": 0.4305555555555556,
223
+ "grad_norm": 34.043235778808594,
224
+ "learning_rate": 1.5500000000000002e-06,
225
+ "loss": 0.4234,
226
+ "step": 31
227
+ },
228
+ {
229
+ "epoch": 0.4444444444444444,
230
+ "grad_norm": 28.703292846679688,
231
+ "learning_rate": 1.6000000000000001e-06,
232
+ "loss": 0.3074,
233
+ "step": 32
234
+ },
235
+ {
236
+ "epoch": 0.4583333333333333,
237
+ "grad_norm": 22.456626892089844,
238
+ "learning_rate": 1.6500000000000003e-06,
239
+ "loss": 0.2146,
240
+ "step": 33
241
+ },
242
+ {
243
+ "epoch": 0.4722222222222222,
244
+ "grad_norm": 15.350156784057617,
245
+ "learning_rate": 1.7000000000000002e-06,
246
+ "loss": 0.1103,
247
+ "step": 34
248
+ },
249
+ {
250
+ "epoch": 0.4861111111111111,
251
+ "grad_norm": 6.5175580978393555,
252
+ "learning_rate": 1.75e-06,
253
+ "loss": 0.0574,
254
+ "step": 35
255
+ },
256
+ {
257
+ "epoch": 0.5,
258
+ "grad_norm": 6.813859939575195,
259
+ "learning_rate": 1.8000000000000001e-06,
260
+ "loss": 0.0497,
261
+ "step": 36
262
+ },
263
+ {
264
+ "epoch": 0.5138888888888888,
265
+ "grad_norm": 3.5350818634033203,
266
+ "learning_rate": 1.85e-06,
267
+ "loss": 0.0199,
268
+ "step": 37
269
+ },
270
+ {
271
+ "epoch": 0.5277777777777778,
272
+ "grad_norm": 4.9657135009765625,
273
+ "learning_rate": 1.9000000000000002e-06,
274
+ "loss": 0.0245,
275
+ "step": 38
276
+ },
277
+ {
278
+ "epoch": 0.5416666666666666,
279
+ "grad_norm": 1.2266570329666138,
280
+ "learning_rate": 1.9500000000000004e-06,
281
+ "loss": 0.0087,
282
+ "step": 39
283
+ },
284
+ {
285
+ "epoch": 0.5555555555555556,
286
+ "grad_norm": 4.982794761657715,
287
+ "learning_rate": 2.0000000000000003e-06,
288
+ "loss": 0.048,
289
+ "step": 40
290
+ },
291
+ {
292
+ "epoch": 0.5694444444444444,
293
+ "grad_norm": 7.6967387199401855,
294
+ "learning_rate": 2.05e-06,
295
+ "loss": 0.0449,
296
+ "step": 41
297
+ },
298
+ {
299
+ "epoch": 0.5833333333333334,
300
+ "grad_norm": 2.9466323852539062,
301
+ "learning_rate": 2.1000000000000002e-06,
302
+ "loss": 0.0098,
303
+ "step": 42
304
+ },
305
+ {
306
+ "epoch": 0.5972222222222222,
307
+ "grad_norm": 2.191035747528076,
308
+ "learning_rate": 2.15e-06,
309
+ "loss": 0.0087,
310
+ "step": 43
311
+ },
312
+ {
313
+ "epoch": 0.6111111111111112,
314
+ "grad_norm": 7.3228840827941895,
315
+ "learning_rate": 2.2e-06,
316
+ "loss": 0.0339,
317
+ "step": 44
318
+ },
319
+ {
320
+ "epoch": 0.625,
321
+ "grad_norm": 4.737412929534912,
322
+ "learning_rate": 2.25e-06,
323
+ "loss": 0.0149,
324
+ "step": 45
325
+ },
326
+ {
327
+ "epoch": 0.6388888888888888,
328
+ "grad_norm": 1.7612887620925903,
329
+ "learning_rate": 2.3000000000000004e-06,
330
+ "loss": 0.0071,
331
+ "step": 46
332
+ },
333
+ {
334
+ "epoch": 0.6527777777777778,
335
+ "grad_norm": 3.344369649887085,
336
+ "learning_rate": 2.35e-06,
337
+ "loss": 0.0196,
338
+ "step": 47
339
+ },
340
+ {
341
+ "epoch": 0.6666666666666666,
342
+ "grad_norm": 2.2957704067230225,
343
+ "learning_rate": 2.4000000000000003e-06,
344
+ "loss": 0.0216,
345
+ "step": 48
346
+ },
347
+ {
348
+ "epoch": 0.6805555555555556,
349
+ "grad_norm": 1.83970308303833,
350
+ "learning_rate": 2.4500000000000003e-06,
351
+ "loss": 0.0221,
352
+ "step": 49
353
+ },
354
+ {
355
+ "epoch": 0.6944444444444444,
356
+ "grad_norm": 1.547287106513977,
357
+ "learning_rate": 2.5e-06,
358
+ "loss": 0.0061,
359
+ "step": 50
360
+ },
361
+ {
362
+ "epoch": 0.7083333333333334,
363
+ "grad_norm": 1.6580262184143066,
364
+ "learning_rate": 2.55e-06,
365
+ "loss": 0.0127,
366
+ "step": 51
367
+ },
368
+ {
369
+ "epoch": 0.7222222222222222,
370
+ "grad_norm": 1.8863849639892578,
371
+ "learning_rate": 2.6e-06,
372
+ "loss": 0.0124,
373
+ "step": 52
374
+ },
375
+ {
376
+ "epoch": 0.7361111111111112,
377
+ "grad_norm": 1.2086963653564453,
378
+ "learning_rate": 2.6500000000000005e-06,
379
+ "loss": 0.0085,
380
+ "step": 53
381
+ },
382
+ {
383
+ "epoch": 0.75,
384
+ "grad_norm": 2.4265427589416504,
385
+ "learning_rate": 2.7000000000000004e-06,
386
+ "loss": 0.0255,
387
+ "step": 54
388
+ },
389
+ {
390
+ "epoch": 0.7638888888888888,
391
+ "grad_norm": 2.0333855152130127,
392
+ "learning_rate": 2.7500000000000004e-06,
393
+ "loss": 0.0145,
394
+ "step": 55
395
+ },
396
+ {
397
+ "epoch": 0.7777777777777778,
398
+ "grad_norm": 2.9129791259765625,
399
+ "learning_rate": 2.8000000000000003e-06,
400
+ "loss": 0.0228,
401
+ "step": 56
402
+ },
403
+ {
404
+ "epoch": 0.7916666666666666,
405
+ "grad_norm": 0.8359552621841431,
406
+ "learning_rate": 2.85e-06,
407
+ "loss": 0.0109,
408
+ "step": 57
409
+ },
410
+ {
411
+ "epoch": 0.8055555555555556,
412
+ "grad_norm": 1.677287220954895,
413
+ "learning_rate": 2.9e-06,
414
+ "loss": 0.0246,
415
+ "step": 58
416
+ },
417
+ {
418
+ "epoch": 0.8194444444444444,
419
+ "grad_norm": 1.0761189460754395,
420
+ "learning_rate": 2.95e-06,
421
+ "loss": 0.0058,
422
+ "step": 59
423
+ },
424
+ {
425
+ "epoch": 0.8333333333333334,
426
+ "grad_norm": 1.1098495721817017,
427
+ "learning_rate": 3e-06,
428
+ "loss": 0.0167,
429
+ "step": 60
430
+ },
431
+ {
432
+ "epoch": 0.8472222222222222,
433
+ "grad_norm": 1.0377463102340698,
434
+ "learning_rate": 3.05e-06,
435
+ "loss": 0.007,
436
+ "step": 61
437
+ },
438
+ {
439
+ "epoch": 0.8611111111111112,
440
+ "grad_norm": 0.6554276347160339,
441
+ "learning_rate": 3.1000000000000004e-06,
442
+ "loss": 0.0039,
443
+ "step": 62
444
+ },
445
+ {
446
+ "epoch": 0.875,
447
+ "grad_norm": 1.279077410697937,
448
+ "learning_rate": 3.1500000000000003e-06,
449
+ "loss": 0.0199,
450
+ "step": 63
451
+ },
452
+ {
453
+ "epoch": 0.8888888888888888,
454
+ "grad_norm": 0.7709833979606628,
455
+ "learning_rate": 3.2000000000000003e-06,
456
+ "loss": 0.0043,
457
+ "step": 64
458
+ },
459
+ {
460
+ "epoch": 0.9027777777777778,
461
+ "grad_norm": 1.3619827032089233,
462
+ "learning_rate": 3.2500000000000002e-06,
463
+ "loss": 0.0067,
464
+ "step": 65
465
+ },
466
+ {
467
+ "epoch": 0.9166666666666666,
468
+ "grad_norm": 1.3849765062332153,
469
+ "learning_rate": 3.3000000000000006e-06,
470
+ "loss": 0.0091,
471
+ "step": 66
472
+ },
473
+ {
474
+ "epoch": 0.9305555555555556,
475
+ "grad_norm": 1.1380351781845093,
476
+ "learning_rate": 3.3500000000000005e-06,
477
+ "loss": 0.0143,
478
+ "step": 67
479
+ },
480
+ {
481
+ "epoch": 0.9444444444444444,
482
+ "grad_norm": 1.9759573936462402,
483
+ "learning_rate": 3.4000000000000005e-06,
484
+ "loss": 0.0231,
485
+ "step": 68
486
+ },
487
+ {
488
+ "epoch": 0.9583333333333334,
489
+ "grad_norm": 0.5920725464820862,
490
+ "learning_rate": 3.45e-06,
491
+ "loss": 0.0063,
492
+ "step": 69
493
+ },
494
+ {
495
+ "epoch": 0.9722222222222222,
496
+ "grad_norm": 1.2489631175994873,
497
+ "learning_rate": 3.5e-06,
498
+ "loss": 0.0149,
499
+ "step": 70
500
+ },
501
+ {
502
+ "epoch": 0.9861111111111112,
503
+ "grad_norm": 1.5553513765335083,
504
+ "learning_rate": 3.5500000000000003e-06,
505
+ "loss": 0.0085,
506
+ "step": 71
507
+ },
508
+ {
509
+ "epoch": 1.0,
510
+ "grad_norm": 1.0278698205947876,
511
+ "learning_rate": 3.6000000000000003e-06,
512
+ "loss": 0.0061,
513
+ "step": 72
514
+ },
515
+ {
516
+ "epoch": 1.0138888888888888,
517
+ "grad_norm": 1.9279776811599731,
518
+ "learning_rate": 3.65e-06,
519
+ "loss": 0.0118,
520
+ "step": 73
521
+ },
522
+ {
523
+ "epoch": 1.0277777777777777,
524
+ "grad_norm": 2.592510223388672,
525
+ "learning_rate": 3.7e-06,
526
+ "loss": 0.0309,
527
+ "step": 74
528
+ },
529
+ {
530
+ "epoch": 1.0416666666666667,
531
+ "grad_norm": 1.6530096530914307,
532
+ "learning_rate": 3.7500000000000005e-06,
533
+ "loss": 0.0099,
534
+ "step": 75
535
+ },
536
+ {
537
+ "epoch": 1.0555555555555556,
538
+ "grad_norm": 0.4624968469142914,
539
+ "learning_rate": 3.8000000000000005e-06,
540
+ "loss": 0.0053,
541
+ "step": 76
542
+ },
543
+ {
544
+ "epoch": 1.0694444444444444,
545
+ "grad_norm": 0.629607617855072,
546
+ "learning_rate": 3.85e-06,
547
+ "loss": 0.0087,
548
+ "step": 77
549
+ },
550
+ {
551
+ "epoch": 1.0833333333333333,
552
+ "grad_norm": 0.14678587019443512,
553
+ "learning_rate": 3.900000000000001e-06,
554
+ "loss": 0.0007,
555
+ "step": 78
556
+ },
557
+ {
558
+ "epoch": 1.0972222222222223,
559
+ "grad_norm": 1.0052955150604248,
560
+ "learning_rate": 3.95e-06,
561
+ "loss": 0.0089,
562
+ "step": 79
563
+ },
564
+ {
565
+ "epoch": 1.1111111111111112,
566
+ "grad_norm": 0.9059052467346191,
567
+ "learning_rate": 4.000000000000001e-06,
568
+ "loss": 0.0049,
569
+ "step": 80
570
+ },
571
+ {
572
+ "epoch": 1.125,
573
+ "grad_norm": 0.871515691280365,
574
+ "learning_rate": 4.05e-06,
575
+ "loss": 0.0092,
576
+ "step": 81
577
+ },
578
+ {
579
+ "epoch": 1.1388888888888888,
580
+ "grad_norm": 0.07520482689142227,
581
+ "learning_rate": 4.1e-06,
582
+ "loss": 0.0004,
583
+ "step": 82
584
+ },
585
+ {
586
+ "epoch": 1.1527777777777777,
587
+ "grad_norm": 0.8039830923080444,
588
+ "learning_rate": 4.15e-06,
589
+ "loss": 0.0031,
590
+ "step": 83
591
+ },
592
+ {
593
+ "epoch": 1.1666666666666667,
594
+ "grad_norm": 0.05209676921367645,
595
+ "learning_rate": 4.2000000000000004e-06,
596
+ "loss": 0.0003,
597
+ "step": 84
598
+ },
599
+ {
600
+ "epoch": 1.1805555555555556,
601
+ "grad_norm": 0.04410432651638985,
602
+ "learning_rate": 4.25e-06,
603
+ "loss": 0.0002,
604
+ "step": 85
605
+ },
606
+ {
607
+ "epoch": 1.1944444444444444,
608
+ "grad_norm": 0.06021099537611008,
609
+ "learning_rate": 4.3e-06,
610
+ "loss": 0.0002,
611
+ "step": 86
612
+ },
613
+ {
614
+ "epoch": 1.2083333333333333,
615
+ "grad_norm": 0.283663272857666,
616
+ "learning_rate": 4.350000000000001e-06,
617
+ "loss": 0.001,
618
+ "step": 87
619
+ },
620
+ {
621
+ "epoch": 1.2222222222222223,
622
+ "grad_norm": 0.6798669695854187,
623
+ "learning_rate": 4.4e-06,
624
+ "loss": 0.0033,
625
+ "step": 88
626
+ },
627
+ {
628
+ "epoch": 1.2361111111111112,
629
+ "grad_norm": 0.06857122480869293,
630
+ "learning_rate": 4.450000000000001e-06,
631
+ "loss": 0.0002,
632
+ "step": 89
633
+ },
634
+ {
635
+ "epoch": 1.25,
636
+ "grad_norm": 1.9897412061691284,
637
+ "learning_rate": 4.5e-06,
638
+ "loss": 0.0126,
639
+ "step": 90
640
+ },
641
+ {
642
+ "epoch": 1.2638888888888888,
643
+ "grad_norm": 1.2174546718597412,
644
+ "learning_rate": 4.5500000000000005e-06,
645
+ "loss": 0.0023,
646
+ "step": 91
647
+ },
648
+ {
649
+ "epoch": 1.2777777777777777,
650
+ "grad_norm": 2.2762115001678467,
651
+ "learning_rate": 4.600000000000001e-06,
652
+ "loss": 0.0095,
653
+ "step": 92
654
+ },
655
+ {
656
+ "epoch": 1.2916666666666667,
657
+ "grad_norm": 3.728581428527832,
658
+ "learning_rate": 4.65e-06,
659
+ "loss": 0.0046,
660
+ "step": 93
661
+ },
662
+ {
663
+ "epoch": 1.3055555555555556,
664
+ "grad_norm": 2.942180871963501,
665
+ "learning_rate": 4.7e-06,
666
+ "loss": 0.0261,
667
+ "step": 94
668
+ },
669
+ {
670
+ "epoch": 1.3194444444444444,
671
+ "grad_norm": 0.3911007344722748,
672
+ "learning_rate": 4.75e-06,
673
+ "loss": 0.0005,
674
+ "step": 95
675
+ },
676
+ {
677
+ "epoch": 1.3333333333333333,
678
+ "grad_norm": 0.03832005336880684,
679
+ "learning_rate": 4.800000000000001e-06,
680
+ "loss": 0.0001,
681
+ "step": 96
682
+ },
683
+ {
684
+ "epoch": 1.3472222222222223,
685
+ "grad_norm": 0.7516991496086121,
686
+ "learning_rate": 4.85e-06,
687
+ "loss": 0.0017,
688
+ "step": 97
689
+ },
690
+ {
691
+ "epoch": 1.3611111111111112,
692
+ "grad_norm": 0.4136435091495514,
693
+ "learning_rate": 4.9000000000000005e-06,
694
+ "loss": 0.0014,
695
+ "step": 98
696
+ },
697
+ {
698
+ "epoch": 1.375,
699
+ "grad_norm": 0.044784627854824066,
700
+ "learning_rate": 4.95e-06,
701
+ "loss": 0.0001,
702
+ "step": 99
703
+ },
704
+ {
705
+ "epoch": 1.3888888888888888,
706
+ "grad_norm": 0.7667476534843445,
707
+ "learning_rate": 5e-06,
708
+ "loss": 0.0022,
709
+ "step": 100
710
+ },
711
+ {
712
+ "epoch": 1.4027777777777777,
713
+ "grad_norm": 0.9187825322151184,
714
+ "learning_rate": 4.999888074163108e-06,
715
+ "loss": 0.0035,
716
+ "step": 101
717
+ },
718
+ {
719
+ "epoch": 1.4166666666666667,
720
+ "grad_norm": 1.2859818935394287,
721
+ "learning_rate": 4.999552306674345e-06,
722
+ "loss": 0.0046,
723
+ "step": 102
724
+ },
725
+ {
726
+ "epoch": 1.4305555555555556,
727
+ "grad_norm": 0.5899283289909363,
728
+ "learning_rate": 4.998992727598557e-06,
729
+ "loss": 0.0027,
730
+ "step": 103
731
+ },
732
+ {
733
+ "epoch": 1.4444444444444444,
734
+ "grad_norm": 0.027552006766200066,
735
+ "learning_rate": 4.998209387040829e-06,
736
+ "loss": 0.0001,
737
+ "step": 104
738
+ },
739
+ {
740
+ "epoch": 1.4583333333333333,
741
+ "grad_norm": 0.14271241426467896,
742
+ "learning_rate": 4.9972023551419995e-06,
743
+ "loss": 0.0002,
744
+ "step": 105
745
+ },
746
+ {
747
+ "epoch": 1.4722222222222223,
748
+ "grad_norm": 0.36476054787635803,
749
+ "learning_rate": 4.995971722072379e-06,
750
+ "loss": 0.001,
751
+ "step": 106
752
+ },
753
+ {
754
+ "epoch": 1.4861111111111112,
755
+ "grad_norm": 1.7742875814437866,
756
+ "learning_rate": 4.9945175980236745e-06,
757
+ "loss": 0.0025,
758
+ "step": 107
759
+ },
760
+ {
761
+ "epoch": 1.5,
762
+ "grad_norm": 0.5356531739234924,
763
+ "learning_rate": 4.992840113199131e-06,
764
+ "loss": 0.0011,
765
+ "step": 108
766
+ },
767
+ {
768
+ "epoch": 1.5138888888888888,
769
+ "grad_norm": 0.9400438070297241,
770
+ "learning_rate": 4.990939417801859e-06,
771
+ "loss": 0.0021,
772
+ "step": 109
773
+ },
774
+ {
775
+ "epoch": 1.5277777777777777,
776
+ "grad_norm": 0.028793074190616608,
777
+ "learning_rate": 4.988815682021398e-06,
778
+ "loss": 0.0001,
779
+ "step": 110
780
+ },
781
+ {
782
+ "epoch": 1.5416666666666665,
783
+ "grad_norm": 0.016167419031262398,
784
+ "learning_rate": 4.986469096018472e-06,
785
+ "loss": 0.0001,
786
+ "step": 111
787
+ },
788
+ {
789
+ "epoch": 1.5555555555555556,
790
+ "grad_norm": 0.04863646626472473,
791
+ "learning_rate": 4.983899869907963e-06,
792
+ "loss": 0.0001,
793
+ "step": 112
794
+ },
795
+ {
796
+ "epoch": 1.5694444444444444,
797
+ "grad_norm": 0.11991345882415771,
798
+ "learning_rate": 4.981108233740096e-06,
799
+ "loss": 0.0003,
800
+ "step": 113
801
+ },
802
+ {
803
+ "epoch": 1.5833333333333335,
804
+ "grad_norm": 1.1984789371490479,
805
+ "learning_rate": 4.978094437479843e-06,
806
+ "loss": 0.0205,
807
+ "step": 114
808
+ },
809
+ {
810
+ "epoch": 1.5972222222222223,
811
+ "grad_norm": 0.2907632887363434,
812
+ "learning_rate": 4.97485875098454e-06,
813
+ "loss": 0.0005,
814
+ "step": 115
815
+ },
816
+ {
817
+ "epoch": 1.6111111111111112,
818
+ "grad_norm": 2.186234474182129,
819
+ "learning_rate": 4.971401463979722e-06,
820
+ "loss": 0.0068,
821
+ "step": 116
822
+ },
823
+ {
824
+ "epoch": 1.625,
825
+ "grad_norm": 0.17205508053302765,
826
+ "learning_rate": 4.967722886033181e-06,
827
+ "loss": 0.0004,
828
+ "step": 117
829
+ },
830
+ {
831
+ "epoch": 1.6388888888888888,
832
+ "grad_norm": 1.9445418119430542,
833
+ "learning_rate": 4.963823346527249e-06,
834
+ "loss": 0.0052,
835
+ "step": 118
836
+ },
837
+ {
838
+ "epoch": 1.6527777777777777,
839
+ "grad_norm": 0.8023346662521362,
840
+ "learning_rate": 4.959703194629304e-06,
841
+ "loss": 0.0087,
842
+ "step": 119
843
+ },
844
+ {
845
+ "epoch": 1.6666666666666665,
846
+ "grad_norm": 0.4967271685600281,
847
+ "learning_rate": 4.955362799260507e-06,
848
+ "loss": 0.0011,
849
+ "step": 120
850
+ },
851
+ {
852
+ "epoch": 1.6805555555555556,
853
+ "grad_norm": 0.18211083114147186,
854
+ "learning_rate": 4.950802549062764e-06,
855
+ "loss": 0.0007,
856
+ "step": 121
857
+ },
858
+ {
859
+ "epoch": 1.6944444444444444,
860
+ "grad_norm": 0.2594281733036041,
861
+ "learning_rate": 4.946022852363932e-06,
862
+ "loss": 0.0011,
863
+ "step": 122
864
+ },
865
+ {
866
+ "epoch": 1.7083333333333335,
867
+ "grad_norm": 0.8132149577140808,
868
+ "learning_rate": 4.9410241371412525e-06,
869
+ "loss": 0.0023,
870
+ "step": 123
871
+ },
872
+ {
873
+ "epoch": 1.7222222222222223,
874
+ "grad_norm": 0.27094146609306335,
875
+ "learning_rate": 4.935806850983034e-06,
876
+ "loss": 0.001,
877
+ "step": 124
878
+ },
879
+ {
880
+ "epoch": 1.7361111111111112,
881
+ "grad_norm": 0.10404836386442184,
882
+ "learning_rate": 4.9303714610485705e-06,
883
+ "loss": 0.0005,
884
+ "step": 125
885
+ },
886
+ {
887
+ "epoch": 1.75,
888
+ "grad_norm": 0.9027087688446045,
889
+ "learning_rate": 4.924718454026318e-06,
890
+ "loss": 0.005,
891
+ "step": 126
892
+ },
893
+ {
894
+ "epoch": 1.7638888888888888,
895
+ "grad_norm": 0.3427490293979645,
896
+ "learning_rate": 4.918848336090309e-06,
897
+ "loss": 0.0013,
898
+ "step": 127
899
+ },
900
+ {
901
+ "epoch": 1.7777777777777777,
902
+ "grad_norm": 0.41760626435279846,
903
+ "learning_rate": 4.912761632854834e-06,
904
+ "loss": 0.0032,
905
+ "step": 128
906
+ },
907
+ {
908
+ "epoch": 1.7916666666666665,
909
+ "grad_norm": 0.09792769700288773,
910
+ "learning_rate": 4.906458889327375e-06,
911
+ "loss": 0.0004,
912
+ "step": 129
913
+ },
914
+ {
915
+ "epoch": 1.8055555555555556,
916
+ "grad_norm": 0.5523985624313354,
917
+ "learning_rate": 4.899940669859807e-06,
918
+ "loss": 0.0077,
919
+ "step": 130
920
+ },
921
+ {
922
+ "epoch": 1.8194444444444444,
923
+ "grad_norm": 0.15261663496494293,
924
+ "learning_rate": 4.893207558097867e-06,
925
+ "loss": 0.0007,
926
+ "step": 131
927
+ },
928
+ {
929
+ "epoch": 1.8333333333333335,
930
+ "grad_norm": 0.12152901291847229,
931
+ "learning_rate": 4.8862601569288885e-06,
932
+ "loss": 0.0005,
933
+ "step": 132
934
+ },
935
+ {
936
+ "epoch": 1.8472222222222223,
937
+ "grad_norm": 0.1660558432340622,
938
+ "learning_rate": 4.879099088427824e-06,
939
+ "loss": 0.0007,
940
+ "step": 133
941
+ },
942
+ {
943
+ "epoch": 1.8611111111111112,
944
+ "grad_norm": 0.45732977986335754,
945
+ "learning_rate": 4.871724993801541e-06,
946
+ "loss": 0.0008,
947
+ "step": 134
948
+ },
949
+ {
950
+ "epoch": 1.875,
951
+ "grad_norm": 0.1277359277009964,
952
+ "learning_rate": 4.864138533331411e-06,
953
+ "loss": 0.0004,
954
+ "step": 135
955
+ },
956
+ {
957
+ "epoch": 1.8888888888888888,
958
+ "grad_norm": 0.08218172937631607,
959
+ "learning_rate": 4.8563403863141825e-06,
960
+ "loss": 0.0003,
961
+ "step": 136
962
+ },
963
+ {
964
+ "epoch": 1.9027777777777777,
965
+ "grad_norm": 0.35776910185813904,
966
+ "learning_rate": 4.84833125100116e-06,
967
+ "loss": 0.0012,
968
+ "step": 137
969
+ },
970
+ {
971
+ "epoch": 1.9166666666666665,
972
+ "grad_norm": 0.11485318094491959,
973
+ "learning_rate": 4.840111844535682e-06,
974
+ "loss": 0.0004,
975
+ "step": 138
976
+ },
977
+ {
978
+ "epoch": 1.9305555555555556,
979
+ "grad_norm": 0.03145573288202286,
980
+ "learning_rate": 4.8316829028889076e-06,
981
+ "loss": 0.0001,
982
+ "step": 139
983
+ },
984
+ {
985
+ "epoch": 1.9444444444444444,
986
+ "grad_norm": 0.03419964388012886,
987
+ "learning_rate": 4.823045180793914e-06,
988
+ "loss": 0.0001,
989
+ "step": 140
990
+ },
991
+ {
992
+ "epoch": 1.9583333333333335,
993
+ "grad_norm": 0.008005158044397831,
994
+ "learning_rate": 4.8141994516781196e-06,
995
+ "loss": 0.0,
996
+ "step": 141
997
+ },
998
+ {
999
+ "epoch": 1.9722222222222223,
1000
+ "grad_norm": 0.30687257647514343,
1001
+ "learning_rate": 4.805146507594034e-06,
1002
+ "loss": 0.0006,
1003
+ "step": 142
1004
+ },
1005
+ {
1006
+ "epoch": 1.9861111111111112,
1007
+ "grad_norm": 0.0030141561292111874,
1008
+ "learning_rate": 4.7958871591483305e-06,
1009
+ "loss": 0.0,
1010
+ "step": 143
1011
+ },
1012
+ {
1013
+ "epoch": 2.0,
1014
+ "grad_norm": 0.0026682906318455935,
1015
+ "learning_rate": 4.786422235429269e-06,
1016
+ "loss": 0.0,
1017
+ "step": 144
1018
+ },
1019
+ {
1020
+ "epoch": 2.013888888888889,
1021
+ "grad_norm": 0.008881614543497562,
1022
+ "learning_rate": 4.776752583932455e-06,
1023
+ "loss": 0.0,
1024
+ "step": 145
1025
+ },
1026
+ {
1027
+ "epoch": 2.0277777777777777,
1028
+ "grad_norm": 0.001991939265280962,
1029
+ "learning_rate": 4.766879070484957e-06,
1030
+ "loss": 0.0,
1031
+ "step": 146
1032
+ },
1033
+ {
1034
+ "epoch": 2.0416666666666665,
1035
+ "grad_norm": 0.006773048546165228,
1036
+ "learning_rate": 4.756802579167781e-06,
1037
+ "loss": 0.0,
1038
+ "step": 147
1039
+ },
1040
+ {
1041
+ "epoch": 2.0555555555555554,
1042
+ "grad_norm": 0.00205055414699018,
1043
+ "learning_rate": 4.746524012236706e-06,
1044
+ "loss": 0.0,
1045
+ "step": 148
1046
+ },
1047
+ {
1048
+ "epoch": 2.0694444444444446,
1049
+ "grad_norm": 0.0041306703351438046,
1050
+ "learning_rate": 4.736044290041496e-06,
1051
+ "loss": 0.0,
1052
+ "step": 149
1053
+ },
1054
+ {
1055
+ "epoch": 2.0833333333333335,
1056
+ "grad_norm": 0.001996932551264763,
1057
+ "learning_rate": 4.725364350943492e-06,
1058
+ "loss": 0.0,
1059
+ "step": 150
1060
+ },
1061
+ {
1062
+ "epoch": 2.0972222222222223,
1063
+ "grad_norm": 0.003478364087641239,
1064
+ "learning_rate": 4.714485151231593e-06,
1065
+ "loss": 0.0,
1066
+ "step": 151
1067
+ },
1068
+ {
1069
+ "epoch": 2.111111111111111,
1070
+ "grad_norm": 0.01027267798781395,
1071
+ "learning_rate": 4.703407665036622e-06,
1072
+ "loss": 0.0,
1073
+ "step": 152
1074
+ },
1075
+ {
1076
+ "epoch": 2.125,
1077
+ "grad_norm": 0.0020006722770631313,
1078
+ "learning_rate": 4.692132884244113e-06,
1079
+ "loss": 0.0,
1080
+ "step": 153
1081
+ },
1082
+ {
1083
+ "epoch": 2.138888888888889,
1084
+ "grad_norm": 0.006151544861495495,
1085
+ "learning_rate": 4.680661818405485e-06,
1086
+ "loss": 0.0,
1087
+ "step": 154
1088
+ },
1089
+ {
1090
+ "epoch": 2.1527777777777777,
1091
+ "grad_norm": 0.0020251101814210415,
1092
+ "learning_rate": 4.668995494647653e-06,
1093
+ "loss": 0.0,
1094
+ "step": 155
1095
+ },
1096
+ {
1097
+ "epoch": 2.1666666666666665,
1098
+ "grad_norm": 0.0021893251687288284,
1099
+ "learning_rate": 4.657134957581057e-06,
1100
+ "loss": 0.0,
1101
+ "step": 156
1102
+ },
1103
+ {
1104
+ "epoch": 2.1805555555555554,
1105
+ "grad_norm": 0.0018878229893743992,
1106
+ "learning_rate": 4.645081269206128e-06,
1107
+ "loss": 0.0,
1108
+ "step": 157
1109
+ },
1110
+ {
1111
+ "epoch": 2.1944444444444446,
1112
+ "grad_norm": 0.759505569934845,
1113
+ "learning_rate": 4.632835508818192e-06,
1114
+ "loss": 0.0002,
1115
+ "step": 158
1116
+ },
1117
+ {
1118
+ "epoch": 2.2083333333333335,
1119
+ "grad_norm": 0.0018357271328568459,
1120
+ "learning_rate": 4.620398772910833e-06,
1121
+ "loss": 0.0,
1122
+ "step": 159
1123
+ },
1124
+ {
1125
+ "epoch": 2.2222222222222223,
1126
+ "grad_norm": 0.001739851082675159,
1127
+ "learning_rate": 4.607772175077712e-06,
1128
+ "loss": 0.0,
1129
+ "step": 160
1130
+ },
1131
+ {
1132
+ "epoch": 2.236111111111111,
1133
+ "grad_norm": 0.0031391726806759834,
1134
+ "learning_rate": 4.59495684591285e-06,
1135
+ "loss": 0.0,
1136
+ "step": 161
1137
+ },
1138
+ {
1139
+ "epoch": 2.25,
1140
+ "grad_norm": 0.001889107865281403,
1141
+ "learning_rate": 4.581953932909403e-06,
1142
+ "loss": 0.0,
1143
+ "step": 162
1144
+ },
1145
+ {
1146
+ "epoch": 2.263888888888889,
1147
+ "grad_norm": 0.0014751956332474947,
1148
+ "learning_rate": 4.5687646003569055e-06,
1149
+ "loss": 0.0,
1150
+ "step": 163
1151
+ },
1152
+ {
1153
+ "epoch": 2.2777777777777777,
1154
+ "grad_norm": 0.0014328192919492722,
1155
+ "learning_rate": 4.555390029237026e-06,
1156
+ "loss": 0.0,
1157
+ "step": 164
1158
+ },
1159
+ {
1160
+ "epoch": 2.2916666666666665,
1161
+ "grad_norm": 0.0014799810014665127,
1162
+ "learning_rate": 4.541831417117815e-06,
1163
+ "loss": 0.0,
1164
+ "step": 165
1165
+ },
1166
+ {
1167
+ "epoch": 2.3055555555555554,
1168
+ "grad_norm": 0.0013504689559340477,
1169
+ "learning_rate": 4.528089978046481e-06,
1170
+ "loss": 0.0,
1171
+ "step": 166
1172
+ },
1173
+ {
1174
+ "epoch": 2.3194444444444446,
1175
+ "grad_norm": 0.001344231073744595,
1176
+ "learning_rate": 4.514166942440679e-06,
1177
+ "loss": 0.0,
1178
+ "step": 167
1179
+ },
1180
+ {
1181
+ "epoch": 2.3333333333333335,
1182
+ "grad_norm": 0.001366922864690423,
1183
+ "learning_rate": 4.5000635569783365e-06,
1184
+ "loss": 0.0,
1185
+ "step": 168
1186
+ },
1187
+ {
1188
+ "epoch": 2.3472222222222223,
1189
+ "grad_norm": 0.0013009505346417427,
1190
+ "learning_rate": 4.4857810844860325e-06,
1191
+ "loss": 0.0,
1192
+ "step": 169
1193
+ },
1194
+ {
1195
+ "epoch": 2.361111111111111,
1196
+ "grad_norm": 0.001247942098416388,
1197
+ "learning_rate": 4.471320803825915e-06,
1198
+ "loss": 0.0,
1199
+ "step": 170
1200
+ },
1201
+ {
1202
+ "epoch": 2.375,
1203
+ "grad_norm": 0.0011512853670865297,
1204
+ "learning_rate": 4.4566840097811956e-06,
1205
+ "loss": 0.0,
1206
+ "step": 171
1207
+ },
1208
+ {
1209
+ "epoch": 2.388888888888889,
1210
+ "grad_norm": 0.001167183741927147,
1211
+ "learning_rate": 4.4418720129402145e-06,
1212
+ "loss": 0.0,
1213
+ "step": 172
1214
+ },
1215
+ {
1216
+ "epoch": 2.4027777777777777,
1217
+ "grad_norm": 0.0011255062418058515,
1218
+ "learning_rate": 4.426886139579083e-06,
1219
+ "loss": 0.0,
1220
+ "step": 173
1221
+ },
1222
+ {
1223
+ "epoch": 2.4166666666666665,
1224
+ "grad_norm": 0.0010559650836512446,
1225
+ "learning_rate": 4.411727731542937e-06,
1226
+ "loss": 0.0,
1227
+ "step": 174
1228
+ },
1229
+ {
1230
+ "epoch": 2.4305555555555554,
1231
+ "grad_norm": 0.0010468937689438462,
1232
+ "learning_rate": 4.39639814612578e-06,
1233
+ "loss": 0.0,
1234
+ "step": 175
1235
+ },
1236
+ {
1237
+ "epoch": 2.4444444444444446,
1238
+ "grad_norm": 0.0009965520584955812,
1239
+ "learning_rate": 4.3808987559489536e-06,
1240
+ "loss": 0.0,
1241
+ "step": 176
1242
+ },
1243
+ {
1244
+ "epoch": 2.4583333333333335,
1245
+ "grad_norm": 0.000950520858168602,
1246
+ "learning_rate": 4.365230948838232e-06,
1247
+ "loss": 0.0,
1248
+ "step": 177
1249
+ },
1250
+ {
1251
+ "epoch": 2.4722222222222223,
1252
+ "grad_norm": 0.0009662396623753011,
1253
+ "learning_rate": 4.349396127699552e-06,
1254
+ "loss": 0.0,
1255
+ "step": 178
1256
+ },
1257
+ {
1258
+ "epoch": 2.486111111111111,
1259
+ "grad_norm": 0.0009316857904195786,
1260
+ "learning_rate": 4.3333957103934025e-06,
1261
+ "loss": 0.0,
1262
+ "step": 179
1263
+ },
1264
+ {
1265
+ "epoch": 2.5,
1266
+ "grad_norm": 0.0009209261042997241,
1267
+ "learning_rate": 4.317231129607859e-06,
1268
+ "loss": 0.0,
1269
+ "step": 180
1270
+ },
1271
+ {
1272
+ "epoch": 2.513888888888889,
1273
+ "grad_norm": 0.0008661423926241696,
1274
+ "learning_rate": 4.30090383273031e-06,
1275
+ "loss": 0.0,
1276
+ "step": 181
1277
+ },
1278
+ {
1279
+ "epoch": 2.5277777777777777,
1280
+ "grad_norm": 0.0008176359115168452,
1281
+ "learning_rate": 4.2844152817178476e-06,
1282
+ "loss": 0.0,
1283
+ "step": 182
1284
+ },
1285
+ {
1286
+ "epoch": 2.5416666666666665,
1287
+ "grad_norm": 0.0008025923161767423,
1288
+ "learning_rate": 4.267766952966369e-06,
1289
+ "loss": 0.0,
1290
+ "step": 183
1291
+ },
1292
+ {
1293
+ "epoch": 2.5555555555555554,
1294
+ "grad_norm": 0.0008243928314186633,
1295
+ "learning_rate": 4.2509603371783776e-06,
1296
+ "loss": 0.0,
1297
+ "step": 184
1298
+ },
1299
+ {
1300
+ "epoch": 2.5694444444444446,
1301
+ "grad_norm": 0.0013688765466213226,
1302
+ "learning_rate": 4.233996939229502e-06,
1303
+ "loss": 0.0,
1304
+ "step": 185
1305
+ },
1306
+ {
1307
+ "epoch": 2.5833333333333335,
1308
+ "grad_norm": 0.0007681425777263939,
1309
+ "learning_rate": 4.216878278033753e-06,
1310
+ "loss": 0.0,
1311
+ "step": 186
1312
+ },
1313
+ {
1314
+ "epoch": 2.5972222222222223,
1315
+ "grad_norm": 0.0007665084558539093,
1316
+ "learning_rate": 4.199605886407515e-06,
1317
+ "loss": 0.0,
1318
+ "step": 187
1319
+ },
1320
+ {
1321
+ "epoch": 2.611111111111111,
1322
+ "grad_norm": 0.000745179713703692,
1323
+ "learning_rate": 4.1821813109322975e-06,
1324
+ "loss": 0.0,
1325
+ "step": 188
1326
+ },
1327
+ {
1328
+ "epoch": 2.625,
1329
+ "grad_norm": 0.0007080566138029099,
1330
+ "learning_rate": 4.164606111816256e-06,
1331
+ "loss": 0.0,
1332
+ "step": 189
1333
+ },
1334
+ {
1335
+ "epoch": 2.638888888888889,
1336
+ "grad_norm": 0.0007035013986751437,
1337
+ "learning_rate": 4.146881862754485e-06,
1338
+ "loss": 0.0,
1339
+ "step": 190
1340
+ },
1341
+ {
1342
+ "epoch": 2.6527777777777777,
1343
+ "grad_norm": 0.001035734312608838,
1344
+ "learning_rate": 4.129010150788112e-06,
1345
+ "loss": 0.0,
1346
+ "step": 191
1347
+ },
1348
+ {
1349
+ "epoch": 2.6666666666666665,
1350
+ "grad_norm": 0.000686554005369544,
1351
+ "learning_rate": 4.110992576162193e-06,
1352
+ "loss": 0.0,
1353
+ "step": 192
1354
+ },
1355
+ {
1356
+ "epoch": 2.6805555555555554,
1357
+ "grad_norm": 0.0006567820673808455,
1358
+ "learning_rate": 4.092830752182423e-06,
1359
+ "loss": 0.0,
1360
+ "step": 193
1361
+ },
1362
+ {
1363
+ "epoch": 2.6944444444444446,
1364
+ "grad_norm": 0.0006689206347800791,
1365
+ "learning_rate": 4.074526305070679e-06,
1366
+ "loss": 0.0,
1367
+ "step": 194
1368
+ },
1369
+ {
1370
+ "epoch": 2.7083333333333335,
1371
+ "grad_norm": 0.000665506231598556,
1372
+ "learning_rate": 4.056080873819412e-06,
1373
+ "loss": 0.0,
1374
+ "step": 195
1375
+ },
1376
+ {
1377
+ "epoch": 2.7222222222222223,
1378
+ "grad_norm": 0.0006280328962020576,
1379
+ "learning_rate": 4.037496110044885e-06,
1380
+ "loss": 0.0,
1381
+ "step": 196
1382
+ },
1383
+ {
1384
+ "epoch": 2.736111111111111,
1385
+ "grad_norm": 0.0005998269189149141,
1386
+ "learning_rate": 4.018773677839289e-06,
1387
+ "loss": 0.0,
1388
+ "step": 197
1389
+ },
1390
+ {
1391
+ "epoch": 2.75,
1392
+ "grad_norm": 0.0007591253379359841,
1393
+ "learning_rate": 3.999915253621739e-06,
1394
+ "loss": 0.0,
1395
+ "step": 198
1396
+ },
1397
+ {
1398
+ "epoch": 2.763888888888889,
1399
+ "grad_norm": 0.0005739334737882018,
1400
+ "learning_rate": 3.980922525988167e-06,
1401
+ "loss": 0.0,
1402
+ "step": 199
1403
+ },
1404
+ {
1405
+ "epoch": 2.7777777777777777,
1406
+ "grad_norm": 0.0005984510062262416,
1407
+ "learning_rate": 3.961797195560118e-06,
1408
+ "loss": 0.0,
1409
+ "step": 200
1410
+ },
1411
+ {
1412
+ "epoch": 2.7916666666666665,
1413
+ "grad_norm": 0.0007093317108228803,
1414
+ "learning_rate": 3.942540974832486e-06,
1415
+ "loss": 0.0,
1416
+ "step": 201
1417
+ },
1418
+ {
1419
+ "epoch": 2.8055555555555554,
1420
+ "grad_norm": 0.0005686501390300691,
1421
+ "learning_rate": 3.9231555880201655e-06,
1422
+ "loss": 0.0,
1423
+ "step": 202
1424
+ },
1425
+ {
1426
+ "epoch": 2.8194444444444446,
1427
+ "grad_norm": 0.0005396155174821615,
1428
+ "learning_rate": 3.903642770903671e-06,
1429
+ "loss": 0.0,
1430
+ "step": 203
1431
+ },
1432
+ {
1433
+ "epoch": 2.8333333333333335,
1434
+ "grad_norm": 0.000549685733858496,
1435
+ "learning_rate": 3.884004270673711e-06,
1436
+ "loss": 0.0,
1437
+ "step": 204
1438
+ },
1439
+ {
1440
+ "epoch": 2.8472222222222223,
1441
+ "grad_norm": 0.0005211409879848361,
1442
+ "learning_rate": 3.864241845774746e-06,
1443
+ "loss": 0.0,
1444
+ "step": 205
1445
+ },
1446
+ {
1447
+ "epoch": 2.861111111111111,
1448
+ "grad_norm": 0.0005807566340081394,
1449
+ "learning_rate": 3.844357265747531e-06,
1450
+ "loss": 0.0,
1451
+ "step": 206
1452
+ },
1453
+ {
1454
+ "epoch": 2.875,
1455
+ "grad_norm": 0.0005310736014507711,
1456
+ "learning_rate": 3.8243523110706736e-06,
1457
+ "loss": 0.0,
1458
+ "step": 207
1459
+ },
1460
+ {
1461
+ "epoch": 2.888888888888889,
1462
+ "grad_norm": 0.001211474766023457,
1463
+ "learning_rate": 3.8042287730012117e-06,
1464
+ "loss": 0.0,
1465
+ "step": 208
1466
+ },
1467
+ {
1468
+ "epoch": 2.9027777777777777,
1469
+ "grad_norm": 0.0005012262845411897,
1470
+ "learning_rate": 3.7839884534142157e-06,
1471
+ "loss": 0.0,
1472
+ "step": 209
1473
+ },
1474
+ {
1475
+ "epoch": 2.9166666666666665,
1476
+ "grad_norm": 0.0005107534816488624,
1477
+ "learning_rate": 3.7636331646414524e-06,
1478
+ "loss": 0.0,
1479
+ "step": 210
1480
+ },
1481
+ {
1482
+ "epoch": 2.9305555555555554,
1483
+ "grad_norm": 0.0005153871607035398,
1484
+ "learning_rate": 3.7431647293091076e-06,
1485
+ "loss": 0.0,
1486
+ "step": 211
1487
+ },
1488
+ {
1489
+ "epoch": 2.9444444444444446,
1490
+ "grad_norm": 0.0005016613868065178,
1491
+ "learning_rate": 3.7225849801745835e-06,
1492
+ "loss": 0.0,
1493
+ "step": 212
1494
+ },
1495
+ {
1496
+ "epoch": 2.9583333333333335,
1497
+ "grad_norm": 0.00048161958693526685,
1498
+ "learning_rate": 3.701895759962397e-06,
1499
+ "loss": 0.0,
1500
+ "step": 213
1501
+ },
1502
+ {
1503
+ "epoch": 2.9722222222222223,
1504
+ "grad_norm": 0.0004826453805435449,
1505
+ "learning_rate": 3.6810989211991777e-06,
1506
+ "loss": 0.0,
1507
+ "step": 214
1508
+ },
1509
+ {
1510
+ "epoch": 2.986111111111111,
1511
+ "grad_norm": 0.0004991457099094987,
1512
+ "learning_rate": 3.6601963260477923e-06,
1513
+ "loss": 0.0,
1514
+ "step": 215
1515
+ },
1516
+ {
1517
+ "epoch": 3.0,
1518
+ "grad_norm": 0.0004765830235555768,
1519
+ "learning_rate": 3.6391898461406045e-06,
1520
+ "loss": 0.0,
1521
+ "step": 216
1522
+ },
1523
+ {
1524
+ "epoch": 3.013888888888889,
1525
+ "grad_norm": 0.0004497554909903556,
1526
+ "learning_rate": 3.6180813624118898e-06,
1527
+ "loss": 0.0,
1528
+ "step": 217
1529
+ },
1530
+ {
1531
+ "epoch": 3.0277777777777777,
1532
+ "grad_norm": 0.001278965501114726,
1533
+ "learning_rate": 3.5968727649294134e-06,
1534
+ "loss": 0.0,
1535
+ "step": 218
1536
+ },
1537
+ {
1538
+ "epoch": 3.0416666666666665,
1539
+ "grad_norm": 0.00046711499453522265,
1540
+ "learning_rate": 3.575565952725193e-06,
1541
+ "loss": 0.0,
1542
+ "step": 219
1543
+ },
1544
+ {
1545
+ "epoch": 3.0555555555555554,
1546
+ "grad_norm": 0.0004580412060022354,
1547
+ "learning_rate": 3.55416283362546e-06,
1548
+ "loss": 0.0,
1549
+ "step": 220
1550
+ },
1551
+ {
1552
+ "epoch": 3.0694444444444446,
1553
+ "grad_norm": 0.0004473453445825726,
1554
+ "learning_rate": 3.5326653240798283e-06,
1555
+ "loss": 0.0,
1556
+ "step": 221
1557
+ },
1558
+ {
1559
+ "epoch": 3.0833333333333335,
1560
+ "grad_norm": 0.00044585420982912183,
1561
+ "learning_rate": 3.5110753489896924e-06,
1562
+ "loss": 0.0,
1563
+ "step": 222
1564
+ },
1565
+ {
1566
+ "epoch": 3.0972222222222223,
1567
+ "grad_norm": 0.00044625229202210903,
1568
+ "learning_rate": 3.4893948415358803e-06,
1569
+ "loss": 0.0,
1570
+ "step": 223
1571
+ },
1572
+ {
1573
+ "epoch": 3.111111111111111,
1574
+ "grad_norm": 0.00042979326099157333,
1575
+ "learning_rate": 3.4676257430055438e-06,
1576
+ "loss": 0.0,
1577
+ "step": 224
1578
+ },
1579
+ {
1580
+ "epoch": 3.125,
1581
+ "grad_norm": 0.0005280164768919349,
1582
+ "learning_rate": 3.4457700026183378e-06,
1583
+ "loss": 0.0,
1584
+ "step": 225
1585
+ },
1586
+ {
1587
+ "epoch": 3.138888888888889,
1588
+ "grad_norm": 0.0004327085625845939,
1589
+ "learning_rate": 3.4238295773518924e-06,
1590
+ "loss": 0.0,
1591
+ "step": 226
1592
+ },
1593
+ {
1594
+ "epoch": 3.1527777777777777,
1595
+ "grad_norm": 0.0004218154354020953,
1596
+ "learning_rate": 3.4018064317665745e-06,
1597
+ "loss": 0.0,
1598
+ "step": 227
1599
+ },
1600
+ {
1601
+ "epoch": 3.1666666666666665,
1602
+ "grad_norm": 0.0004269857599865645,
1603
+ "learning_rate": 3.3797025378295826e-06,
1604
+ "loss": 0.0,
1605
+ "step": 228
1606
+ },
1607
+ {
1608
+ "epoch": 3.1805555555555554,
1609
+ "grad_norm": 0.0004188821476418525,
1610
+ "learning_rate": 3.357519874738382e-06,
1611
+ "loss": 0.0,
1612
+ "step": 229
1613
+ },
1614
+ {
1615
+ "epoch": 3.1944444444444446,
1616
+ "grad_norm": 0.00043003325117751956,
1617
+ "learning_rate": 3.3352604287434752e-06,
1618
+ "loss": 0.0,
1619
+ "step": 230
1620
+ },
1621
+ {
1622
+ "epoch": 3.2083333333333335,
1623
+ "grad_norm": 0.00041776004945859313,
1624
+ "learning_rate": 3.31292619297056e-06,
1625
+ "loss": 0.0,
1626
+ "step": 231
1627
+ },
1628
+ {
1629
+ "epoch": 3.2222222222222223,
1630
+ "grad_norm": 0.0004131250607315451,
1631
+ "learning_rate": 3.29051916724206e-06,
1632
+ "loss": 0.0,
1633
+ "step": 232
1634
+ },
1635
+ {
1636
+ "epoch": 3.236111111111111,
1637
+ "grad_norm": 0.0004490792634896934,
1638
+ "learning_rate": 3.2680413578980623e-06,
1639
+ "loss": 0.0,
1640
+ "step": 233
1641
+ },
1642
+ {
1643
+ "epoch": 3.25,
1644
+ "grad_norm": 0.00040265225106850266,
1645
+ "learning_rate": 3.245494777616664e-06,
1646
+ "loss": 0.0,
1647
+ "step": 234
1648
+ },
1649
+ {
1650
+ "epoch": 3.263888888888889,
1651
+ "grad_norm": 0.0003899024159181863,
1652
+ "learning_rate": 3.2228814452337587e-06,
1653
+ "loss": 0.0,
1654
+ "step": 235
1655
+ },
1656
+ {
1657
+ "epoch": 3.2777777777777777,
1658
+ "grad_norm": 0.00039753629243932664,
1659
+ "learning_rate": 3.2002033855622683e-06,
1660
+ "loss": 0.0,
1661
+ "step": 236
1662
+ },
1663
+ {
1664
+ "epoch": 3.2916666666666665,
1665
+ "grad_norm": 0.00041745221824385226,
1666
+ "learning_rate": 3.177462629210838e-06,
1667
+ "loss": 0.0,
1668
+ "step": 237
1669
+ },
1670
+ {
1671
+ "epoch": 3.3055555555555554,
1672
+ "grad_norm": 0.00037628141581080854,
1673
+ "learning_rate": 3.154661212402017e-06,
1674
+ "loss": 0.0,
1675
+ "step": 238
1676
+ },
1677
+ {
1678
+ "epoch": 3.3194444444444446,
1679
+ "grad_norm": 0.0004110137524548918,
1680
+ "learning_rate": 3.131801176789934e-06,
1681
+ "loss": 0.0,
1682
+ "step": 239
1683
+ },
1684
+ {
1685
+ "epoch": 3.3333333333333335,
1686
+ "grad_norm": 0.0003878215211443603,
1687
+ "learning_rate": 3.1088845692774798e-06,
1688
+ "loss": 0.0,
1689
+ "step": 240
1690
+ },
1691
+ {
1692
+ "epoch": 3.3472222222222223,
1693
+ "grad_norm": 0.0004746608901768923,
1694
+ "learning_rate": 3.0859134418330373e-06,
1695
+ "loss": 0.0,
1696
+ "step": 241
1697
+ },
1698
+ {
1699
+ "epoch": 3.361111111111111,
1700
+ "grad_norm": 0.0017198650166392326,
1701
+ "learning_rate": 3.0628898513067357e-06,
1702
+ "loss": 0.0,
1703
+ "step": 242
1704
+ },
1705
+ {
1706
+ "epoch": 3.375,
1707
+ "grad_norm": 0.00038812440470792353,
1708
+ "learning_rate": 3.0398158592462847e-06,
1709
+ "loss": 0.0,
1710
+ "step": 243
1711
+ },
1712
+ {
1713
+ "epoch": 3.388888888888889,
1714
+ "grad_norm": 0.0003960718458984047,
1715
+ "learning_rate": 3.0166935317123824e-06,
1716
+ "loss": 0.0,
1717
+ "step": 244
1718
+ },
1719
+ {
1720
+ "epoch": 3.4027777777777777,
1721
+ "grad_norm": 0.0003934325650334358,
1722
+ "learning_rate": 2.9935249390937184e-06,
1723
+ "loss": 0.0,
1724
+ "step": 245
1725
+ },
1726
+ {
1727
+ "epoch": 3.4166666666666665,
1728
+ "grad_norm": 0.0003809865447692573,
1729
+ "learning_rate": 2.970312155921585e-06,
1730
+ "loss": 0.0,
1731
+ "step": 246
1732
+ },
1733
+ {
1734
+ "epoch": 3.4305555555555554,
1735
+ "grad_norm": 0.0003733540652319789,
1736
+ "learning_rate": 2.9470572606841295e-06,
1737
+ "loss": 0.0,
1738
+ "step": 247
1739
+ },
1740
+ {
1741
+ "epoch": 3.4444444444444446,
1742
+ "grad_norm": 0.0007575592026114464,
1743
+ "learning_rate": 2.9237623356402423e-06,
1744
+ "loss": 0.0,
1745
+ "step": 248
1746
+ },
1747
+ {
1748
+ "epoch": 3.4583333333333335,
1749
+ "grad_norm": 0.0003538963501341641,
1750
+ "learning_rate": 2.900429466633107e-06,
1751
+ "loss": 0.0,
1752
+ "step": 249
1753
+ },
1754
+ {
1755
+ "epoch": 3.4722222222222223,
1756
+ "grad_norm": 0.00036024293513037264,
1757
+ "learning_rate": 2.8770607429034352e-06,
1758
+ "loss": 0.0,
1759
+ "step": 250
1760
+ },
1761
+ {
1762
+ "epoch": 3.486111111111111,
1763
+ "grad_norm": 0.0003511797694955021,
1764
+ "learning_rate": 2.8536582569023964e-06,
1765
+ "loss": 0.0,
1766
+ "step": 251
1767
+ },
1768
+ {
1769
+ "epoch": 3.5,
1770
+ "grad_norm": 0.00034679597592912614,
1771
+ "learning_rate": 2.8302241041042564e-06,
1772
+ "loss": 0.0,
1773
+ "step": 252
1774
+ },
1775
+ {
1776
+ "epoch": 3.513888888888889,
1777
+ "grad_norm": 0.00037080422043800354,
1778
+ "learning_rate": 2.8067603828187446e-06,
1779
+ "loss": 0.0,
1780
+ "step": 253
1781
+ },
1782
+ {
1783
+ "epoch": 3.5277777777777777,
1784
+ "grad_norm": 0.0003417868574615568,
1785
+ "learning_rate": 2.7832691940031755e-06,
1786
+ "loss": 0.0,
1787
+ "step": 254
1788
+ },
1789
+ {
1790
+ "epoch": 3.5416666666666665,
1791
+ "grad_norm": 0.00034637749195098877,
1792
+ "learning_rate": 2.759752641074322e-06,
1793
+ "loss": 0.0,
1794
+ "step": 255
1795
+ },
1796
+ {
1797
+ "epoch": 3.5555555555555554,
1798
+ "grad_norm": 0.00035772964474745095,
1799
+ "learning_rate": 2.7362128297200784e-06,
1800
+ "loss": 0.0,
1801
+ "step": 256
1802
+ },
1803
+ {
1804
+ "epoch": 3.5694444444444446,
1805
+ "grad_norm": 0.00034110111300833523,
1806
+ "learning_rate": 2.712651867710914e-06,
1807
+ "loss": 0.0,
1808
+ "step": 257
1809
+ },
1810
+ {
1811
+ "epoch": 3.5833333333333335,
1812
+ "grad_norm": 0.00033183529740199447,
1813
+ "learning_rate": 2.6890718647111424e-06,
1814
+ "loss": 0.0,
1815
+ "step": 258
1816
+ },
1817
+ {
1818
+ "epoch": 3.5972222222222223,
1819
+ "grad_norm": 0.00034375995164737105,
1820
+ "learning_rate": 2.665474932090017e-06,
1821
+ "loss": 0.0,
1822
+ "step": 259
1823
+ },
1824
+ {
1825
+ "epoch": 3.611111111111111,
1826
+ "grad_norm": 0.0003534927382133901,
1827
+ "learning_rate": 2.6418631827326857e-06,
1828
+ "loss": 0.0,
1829
+ "step": 260
1830
+ },
1831
+ {
1832
+ "epoch": 3.625,
1833
+ "grad_norm": 0.00034480984322726727,
1834
+ "learning_rate": 2.6182387308509927e-06,
1835
+ "loss": 0.0,
1836
+ "step": 261
1837
+ },
1838
+ {
1839
+ "epoch": 3.638888888888889,
1840
+ "grad_norm": 0.00034357619006186724,
1841
+ "learning_rate": 2.5946036917941765e-06,
1842
+ "loss": 0.0,
1843
+ "step": 262
1844
+ },
1845
+ {
1846
+ "epoch": 3.6527777777777777,
1847
+ "grad_norm": 0.0003348125028423965,
1848
+ "learning_rate": 2.570960181859458e-06,
1849
+ "loss": 0.0,
1850
+ "step": 263
1851
+ },
1852
+ {
1853
+ "epoch": 3.6666666666666665,
1854
+ "grad_norm": 0.0003396561951376498,
1855
+ "learning_rate": 2.547310318102548e-06,
1856
+ "loss": 0.0,
1857
+ "step": 264
1858
+ },
1859
+ {
1860
+ "epoch": 3.6805555555555554,
1861
+ "grad_norm": 0.000327035115333274,
1862
+ "learning_rate": 2.5236562181480794e-06,
1863
+ "loss": 0.0,
1864
+ "step": 265
1865
+ },
1866
+ {
1867
+ "epoch": 3.6944444444444446,
1868
+ "grad_norm": 0.0012853932566940784,
1869
+ "learning_rate": 2.5e-06,
1870
+ "loss": 0.0,
1871
+ "step": 266
1872
+ },
1873
+ {
1874
+ "epoch": 3.7083333333333335,
1875
+ "grad_norm": 0.00033309016725979745,
1876
+ "learning_rate": 2.4763437818519205e-06,
1877
+ "loss": 0.0,
1878
+ "step": 267
1879
+ },
1880
+ {
1881
+ "epoch": 3.7222222222222223,
1882
+ "grad_norm": 0.0003192981530446559,
1883
+ "learning_rate": 2.4526896818974534e-06,
1884
+ "loss": 0.0,
1885
+ "step": 268
1886
+ },
1887
+ {
1888
+ "epoch": 3.736111111111111,
1889
+ "grad_norm": 0.00032640976132825017,
1890
+ "learning_rate": 2.429039818140543e-06,
1891
+ "loss": 0.0,
1892
+ "step": 269
1893
+ },
1894
+ {
1895
+ "epoch": 3.75,
1896
+ "grad_norm": 0.00033392352634109557,
1897
+ "learning_rate": 2.405396308205825e-06,
1898
+ "loss": 0.0,
1899
+ "step": 270
1900
+ },
1901
+ {
1902
+ "epoch": 3.763888888888889,
1903
+ "grad_norm": 0.0003594683366827667,
1904
+ "learning_rate": 2.381761269149009e-06,
1905
+ "loss": 0.0,
1906
+ "step": 271
1907
+ },
1908
+ {
1909
+ "epoch": 3.7777777777777777,
1910
+ "grad_norm": 0.010392317548394203,
1911
+ "learning_rate": 2.358136817267315e-06,
1912
+ "loss": 0.0,
1913
+ "step": 272
1914
+ },
1915
+ {
1916
+ "epoch": 3.7916666666666665,
1917
+ "grad_norm": 0.00031630549347028136,
1918
+ "learning_rate": 2.334525067909983e-06,
1919
+ "loss": 0.0,
1920
+ "step": 273
1921
+ },
1922
+ {
1923
+ "epoch": 3.8055555555555554,
1924
+ "grad_norm": 0.0003196642210241407,
1925
+ "learning_rate": 2.3109281352888593e-06,
1926
+ "loss": 0.0,
1927
+ "step": 274
1928
+ },
1929
+ {
1930
+ "epoch": 3.8194444444444446,
1931
+ "grad_norm": 0.00031541771022602916,
1932
+ "learning_rate": 2.2873481322890866e-06,
1933
+ "loss": 0.0,
1934
+ "step": 275
1935
+ },
1936
+ {
1937
+ "epoch": 3.8333333333333335,
1938
+ "grad_norm": 0.0003151163400616497,
1939
+ "learning_rate": 2.263787170279922e-06,
1940
+ "loss": 0.0,
1941
+ "step": 276
1942
+ },
1943
+ {
1944
+ "epoch": 3.8472222222222223,
1945
+ "grad_norm": 0.0003220181097276509,
1946
+ "learning_rate": 2.2402473589256793e-06,
1947
+ "loss": 0.0,
1948
+ "step": 277
1949
+ },
1950
+ {
1951
+ "epoch": 3.861111111111111,
1952
+ "grad_norm": 0.00031665421556681395,
1953
+ "learning_rate": 2.2167308059968258e-06,
1954
+ "loss": 0.0,
1955
+ "step": 278
1956
+ },
1957
+ {
1958
+ "epoch": 3.875,
1959
+ "grad_norm": 0.0003038264694623649,
1960
+ "learning_rate": 2.193239617181256e-06,
1961
+ "loss": 0.0,
1962
+ "step": 279
1963
+ },
1964
+ {
1965
+ "epoch": 3.888888888888889,
1966
+ "grad_norm": 0.00031601826776750386,
1967
+ "learning_rate": 2.169775895895745e-06,
1968
+ "loss": 0.0,
1969
+ "step": 280
1970
+ },
1971
+ {
1972
+ "epoch": 3.9027777777777777,
1973
+ "grad_norm": 0.0003112203849013895,
1974
+ "learning_rate": 2.146341743097604e-06,
1975
+ "loss": 0.0,
1976
+ "step": 281
1977
+ },
1978
+ {
1979
+ "epoch": 3.9166666666666665,
1980
+ "grad_norm": 0.00030921402503736317,
1981
+ "learning_rate": 2.1229392570965656e-06,
1982
+ "loss": 0.0,
1983
+ "step": 282
1984
+ },
1985
+ {
1986
+ "epoch": 3.9305555555555554,
1987
+ "grad_norm": 0.00031801871955394745,
1988
+ "learning_rate": 2.0995705333668948e-06,
1989
+ "loss": 0.0,
1990
+ "step": 283
1991
+ },
1992
+ {
1993
+ "epoch": 3.9444444444444446,
1994
+ "grad_norm": 0.0003068145888391882,
1995
+ "learning_rate": 2.0762376643597586e-06,
1996
+ "loss": 0.0,
1997
+ "step": 284
1998
+ },
1999
+ {
2000
+ "epoch": 3.9583333333333335,
2001
+ "grad_norm": 0.000303666980471462,
2002
+ "learning_rate": 2.0529427393158704e-06,
2003
+ "loss": 0.0,
2004
+ "step": 285
2005
+ },
2006
+ {
2007
+ "epoch": 3.9722222222222223,
2008
+ "grad_norm": 0.00037687006988562644,
2009
+ "learning_rate": 2.0296878440784164e-06,
2010
+ "loss": 0.0,
2011
+ "step": 286
2012
+ },
2013
+ {
2014
+ "epoch": 3.986111111111111,
2015
+ "grad_norm": 0.0004179875541012734,
2016
+ "learning_rate": 2.006475060906283e-06,
2017
+ "loss": 0.0,
2018
+ "step": 287
2019
+ },
2020
+ {
2021
+ "epoch": 4.0,
2022
+ "grad_norm": 0.00030332262394949794,
2023
+ "learning_rate": 1.9833064682876175e-06,
2024
+ "loss": 0.0,
2025
+ "step": 288
2026
+ },
2027
+ {
2028
+ "epoch": 4.013888888888889,
2029
+ "grad_norm": 0.000312824355205521,
2030
+ "learning_rate": 1.9601841407537157e-06,
2031
+ "loss": 0.0,
2032
+ "step": 289
2033
+ },
2034
+ {
2035
+ "epoch": 4.027777777777778,
2036
+ "grad_norm": 0.0008900280809029937,
2037
+ "learning_rate": 1.937110148693265e-06,
2038
+ "loss": 0.0,
2039
+ "step": 290
2040
+ },
2041
+ {
2042
+ "epoch": 4.041666666666667,
2043
+ "grad_norm": 0.00030201984918676317,
2044
+ "learning_rate": 1.9140865581669627e-06,
2045
+ "loss": 0.0,
2046
+ "step": 291
2047
+ },
2048
+ {
2049
+ "epoch": 4.055555555555555,
2050
+ "grad_norm": 0.00037866891943849623,
2051
+ "learning_rate": 1.8911154307225204e-06,
2052
+ "loss": 0.0,
2053
+ "step": 292
2054
+ },
2055
+ {
2056
+ "epoch": 4.069444444444445,
2057
+ "grad_norm": 0.0003057627473026514,
2058
+ "learning_rate": 1.8681988232100674e-06,
2059
+ "loss": 0.0,
2060
+ "step": 293
2061
+ },
2062
+ {
2063
+ "epoch": 4.083333333333333,
2064
+ "grad_norm": 0.0003006605838891119,
2065
+ "learning_rate": 1.8453387875979834e-06,
2066
+ "loss": 0.0,
2067
+ "step": 294
2068
+ },
2069
+ {
2070
+ "epoch": 4.097222222222222,
2071
+ "grad_norm": 0.0003039598523173481,
2072
+ "learning_rate": 1.822537370789163e-06,
2073
+ "loss": 0.0,
2074
+ "step": 295
2075
+ },
2076
+ {
2077
+ "epoch": 4.111111111111111,
2078
+ "grad_norm": 0.00030075316317379475,
2079
+ "learning_rate": 1.7997966144377328e-06,
2080
+ "loss": 0.0,
2081
+ "step": 296
2082
+ },
2083
+ {
2084
+ "epoch": 4.125,
2085
+ "grad_norm": 0.0005559928831644356,
2086
+ "learning_rate": 1.7771185547662417e-06,
2087
+ "loss": 0.0,
2088
+ "step": 297
2089
+ },
2090
+ {
2091
+ "epoch": 4.138888888888889,
2092
+ "grad_norm": 0.0003315582871437073,
2093
+ "learning_rate": 1.754505222383337e-06,
2094
+ "loss": 0.0,
2095
+ "step": 298
2096
+ },
2097
+ {
2098
+ "epoch": 4.152777777777778,
2099
+ "grad_norm": 0.00028943977667950094,
2100
+ "learning_rate": 1.7319586421019383e-06,
2101
+ "loss": 0.0,
2102
+ "step": 299
2103
+ },
2104
+ {
2105
+ "epoch": 4.166666666666667,
2106
+ "grad_norm": 0.0003514060808811337,
2107
+ "learning_rate": 1.7094808327579401e-06,
2108
+ "loss": 0.0,
2109
+ "step": 300
2110
+ },
2111
+ {
2112
+ "epoch": 4.180555555555555,
2113
+ "grad_norm": 0.00029012124286964536,
2114
+ "learning_rate": 1.6870738070294412e-06,
2115
+ "loss": 0.0,
2116
+ "step": 301
2117
+ },
2118
+ {
2119
+ "epoch": 4.194444444444445,
2120
+ "grad_norm": 0.000285898830043152,
2121
+ "learning_rate": 1.6647395712565256e-06,
2122
+ "loss": 0.0,
2123
+ "step": 302
2124
+ },
2125
+ {
2126
+ "epoch": 4.208333333333333,
2127
+ "grad_norm": 0.0002975537208840251,
2128
+ "learning_rate": 1.6424801252616186e-06,
2129
+ "loss": 0.0,
2130
+ "step": 303
2131
+ },
2132
+ {
2133
+ "epoch": 4.222222222222222,
2134
+ "grad_norm": 0.00029446210828609765,
2135
+ "learning_rate": 1.6202974621704176e-06,
2136
+ "loss": 0.0,
2137
+ "step": 304
2138
+ },
2139
+ {
2140
+ "epoch": 4.236111111111111,
2141
+ "grad_norm": 0.0002837205829564482,
2142
+ "learning_rate": 1.5981935682334266e-06,
2143
+ "loss": 0.0,
2144
+ "step": 305
2145
+ },
2146
+ {
2147
+ "epoch": 4.25,
2148
+ "grad_norm": 0.0002935337251983583,
2149
+ "learning_rate": 1.5761704226481078e-06,
2150
+ "loss": 0.0,
2151
+ "step": 306
2152
+ },
2153
+ {
2154
+ "epoch": 4.263888888888889,
2155
+ "grad_norm": 0.00029275196720846,
2156
+ "learning_rate": 1.5542299973816626e-06,
2157
+ "loss": 0.0,
2158
+ "step": 307
2159
+ },
2160
+ {
2161
+ "epoch": 4.277777777777778,
2162
+ "grad_norm": 0.00029929872835054994,
2163
+ "learning_rate": 1.5323742569944573e-06,
2164
+ "loss": 0.0,
2165
+ "step": 308
2166
+ },
2167
+ {
2168
+ "epoch": 4.291666666666667,
2169
+ "grad_norm": 0.00028991978615522385,
2170
+ "learning_rate": 1.5106051584641208e-06,
2171
+ "loss": 0.0,
2172
+ "step": 309
2173
+ },
2174
+ {
2175
+ "epoch": 4.305555555555555,
2176
+ "grad_norm": 0.0002811246959026903,
2177
+ "learning_rate": 1.4889246510103078e-06,
2178
+ "loss": 0.0,
2179
+ "step": 310
2180
+ },
2181
+ {
2182
+ "epoch": 4.319444444444445,
2183
+ "grad_norm": 0.00028082230710424483,
2184
+ "learning_rate": 1.4673346759201728e-06,
2185
+ "loss": 0.0,
2186
+ "step": 311
2187
+ },
2188
+ {
2189
+ "epoch": 4.333333333333333,
2190
+ "grad_norm": 0.0002810833975672722,
2191
+ "learning_rate": 1.44583716637454e-06,
2192
+ "loss": 0.0,
2193
+ "step": 312
2194
+ },
2195
+ {
2196
+ "epoch": 4.347222222222222,
2197
+ "grad_norm": 0.00030640949262306094,
2198
+ "learning_rate": 1.4244340472748076e-06,
2199
+ "loss": 0.0,
2200
+ "step": 313
2201
+ },
2202
+ {
2203
+ "epoch": 4.361111111111111,
2204
+ "grad_norm": 0.00027884720475412905,
2205
+ "learning_rate": 1.403127235070587e-06,
2206
+ "loss": 0.0,
2207
+ "step": 314
2208
+ },
2209
+ {
2210
+ "epoch": 4.375,
2211
+ "grad_norm": 0.00028082833159714937,
2212
+ "learning_rate": 1.381918637588112e-06,
2213
+ "loss": 0.0,
2214
+ "step": 315
2215
+ },
2216
+ {
2217
+ "epoch": 4.388888888888889,
2218
+ "grad_norm": 0.00028363679302856326,
2219
+ "learning_rate": 1.3608101538593965e-06,
2220
+ "loss": 0.0,
2221
+ "step": 316
2222
+ },
2223
+ {
2224
+ "epoch": 4.402777777777778,
2225
+ "grad_norm": 0.00027668694383464754,
2226
+ "learning_rate": 1.3398036739522088e-06,
2227
+ "loss": 0.0,
2228
+ "step": 317
2229
+ },
2230
+ {
2231
+ "epoch": 4.416666666666667,
2232
+ "grad_norm": 0.00028155132895335555,
2233
+ "learning_rate": 1.3189010788008234e-06,
2234
+ "loss": 0.0,
2235
+ "step": 318
2236
+ },
2237
+ {
2238
+ "epoch": 4.430555555555555,
2239
+ "grad_norm": 0.0007724284077994525,
2240
+ "learning_rate": 1.2981042400376032e-06,
2241
+ "loss": 0.0,
2242
+ "step": 319
2243
+ },
2244
+ {
2245
+ "epoch": 4.444444444444445,
2246
+ "grad_norm": 0.00036324880784377456,
2247
+ "learning_rate": 1.277415019825417e-06,
2248
+ "loss": 0.0,
2249
+ "step": 320
2250
+ },
2251
+ {
2252
+ "epoch": 4.458333333333333,
2253
+ "grad_norm": 0.00027311878511682153,
2254
+ "learning_rate": 1.2568352706908937e-06,
2255
+ "loss": 0.0,
2256
+ "step": 321
2257
+ },
2258
+ {
2259
+ "epoch": 4.472222222222222,
2260
+ "grad_norm": 0.0002935140219051391,
2261
+ "learning_rate": 1.2363668353585486e-06,
2262
+ "loss": 0.0,
2263
+ "step": 322
2264
+ },
2265
+ {
2266
+ "epoch": 4.486111111111111,
2267
+ "grad_norm": 0.0002762887452263385,
2268
+ "learning_rate": 1.216011546585785e-06,
2269
+ "loss": 0.0,
2270
+ "step": 323
2271
+ },
2272
+ {
2273
+ "epoch": 4.5,
2274
+ "grad_norm": 0.00029656346305273473,
2275
+ "learning_rate": 1.195771226998789e-06,
2276
+ "loss": 0.0,
2277
+ "step": 324
2278
+ },
2279
+ {
2280
+ "epoch": 4.513888888888889,
2281
+ "grad_norm": 0.0002801907539833337,
2282
+ "learning_rate": 1.1756476889293269e-06,
2283
+ "loss": 0.0,
2284
+ "step": 325
2285
+ },
2286
+ {
2287
+ "epoch": 4.527777777777778,
2288
+ "grad_norm": 0.0002702914352994412,
2289
+ "learning_rate": 1.1556427342524698e-06,
2290
+ "loss": 0.0,
2291
+ "step": 326
2292
+ },
2293
+ {
2294
+ "epoch": 4.541666666666667,
2295
+ "grad_norm": 0.0002727097016759217,
2296
+ "learning_rate": 1.1357581542252555e-06,
2297
+ "loss": 0.0,
2298
+ "step": 327
2299
+ },
2300
+ {
2301
+ "epoch": 4.555555555555555,
2302
+ "grad_norm": 0.0002765726239886135,
2303
+ "learning_rate": 1.1159957293262888e-06,
2304
+ "loss": 0.0,
2305
+ "step": 328
2306
+ },
2307
+ {
2308
+ "epoch": 4.569444444444445,
2309
+ "grad_norm": 0.0002687490778043866,
2310
+ "learning_rate": 1.0963572290963298e-06,
2311
+ "loss": 0.0,
2312
+ "step": 329
2313
+ },
2314
+ {
2315
+ "epoch": 4.583333333333333,
2316
+ "grad_norm": 0.0002718923205975443,
2317
+ "learning_rate": 1.0768444119798357e-06,
2318
+ "loss": 0.0,
2319
+ "step": 330
2320
+ },
2321
+ {
2322
+ "epoch": 4.597222222222222,
2323
+ "grad_norm": 0.0003026482881978154,
2324
+ "learning_rate": 1.0574590251675145e-06,
2325
+ "loss": 0.0,
2326
+ "step": 331
2327
+ },
2328
+ {
2329
+ "epoch": 4.611111111111111,
2330
+ "grad_norm": 0.00027299264911562204,
2331
+ "learning_rate": 1.0382028044398823e-06,
2332
+ "loss": 0.0,
2333
+ "step": 332
2334
+ },
2335
+ {
2336
+ "epoch": 4.625,
2337
+ "grad_norm": 0.00026989809703081846,
2338
+ "learning_rate": 1.0190774740118343e-06,
2339
+ "loss": 0.0,
2340
+ "step": 333
2341
+ },
2342
+ {
2343
+ "epoch": 4.638888888888889,
2344
+ "grad_norm": 0.00028061502962373197,
2345
+ "learning_rate": 1.0000847463782615e-06,
2346
+ "loss": 0.0,
2347
+ "step": 334
2348
+ },
2349
+ {
2350
+ "epoch": 4.652777777777778,
2351
+ "grad_norm": 0.0002712835557758808,
2352
+ "learning_rate": 9.812263221607114e-07,
2353
+ "loss": 0.0,
2354
+ "step": 335
2355
+ },
2356
+ {
2357
+ "epoch": 4.666666666666667,
2358
+ "grad_norm": 0.0002652051334735006,
2359
+ "learning_rate": 9.625038899551162e-07,
2360
+ "loss": 0.0,
2361
+ "step": 336
2362
+ },
2363
+ {
2364
+ "epoch": 4.680555555555555,
2365
+ "grad_norm": 0.00044494643225334585,
2366
+ "learning_rate": 9.439191261805894e-07,
2367
+ "loss": 0.0,
2368
+ "step": 337
2369
+ },
2370
+ {
2371
+ "epoch": 4.694444444444445,
2372
+ "grad_norm": 0.00026834887103177607,
2373
+ "learning_rate": 9.254736949293216e-07,
2374
+ "loss": 0.0,
2375
+ "step": 338
2376
+ },
2377
+ {
2378
+ "epoch": 4.708333333333333,
2379
+ "grad_norm": 0.00030554624390788376,
2380
+ "learning_rate": 9.07169247817579e-07,
2381
+ "loss": 0.0,
2382
+ "step": 339
2383
+ },
2384
+ {
2385
+ "epoch": 4.722222222222222,
2386
+ "grad_norm": 0.00027393290656618774,
2387
+ "learning_rate": 8.890074238378074e-07,
2388
+ "loss": 0.0,
2389
+ "step": 340
2390
+ },
2391
+ {
2392
+ "epoch": 4.736111111111111,
2393
+ "grad_norm": 0.0012748402077704668,
2394
+ "learning_rate": 8.709898492118885e-07,
2395
+ "loss": 0.0,
2396
+ "step": 341
2397
+ },
2398
+ {
2399
+ "epoch": 4.75,
2400
+ "grad_norm": 0.0002683771017473191,
2401
+ "learning_rate": 8.531181372455161e-07,
2402
+ "loss": 0.0,
2403
+ "step": 342
2404
+ },
2405
+ {
2406
+ "epoch": 4.763888888888889,
2407
+ "grad_norm": 0.0002686232910491526,
2408
+ "learning_rate": 8.353938881837445e-07,
2409
+ "loss": 0.0,
2410
+ "step": 343
2411
+ },
2412
+ {
2413
+ "epoch": 4.777777777777778,
2414
+ "grad_norm": 0.0002642960462253541,
2415
+ "learning_rate": 8.178186890677029e-07,
2416
+ "loss": 0.0,
2417
+ "step": 344
2418
+ },
2419
+ {
2420
+ "epoch": 4.791666666666667,
2421
+ "grad_norm": 0.00026234518736600876,
2422
+ "learning_rate": 8.003941135924859e-07,
2423
+ "loss": 0.0,
2424
+ "step": 345
2425
+ },
2426
+ {
2427
+ "epoch": 4.805555555555555,
2428
+ "grad_norm": 0.0002638711594045162,
2429
+ "learning_rate": 7.83121721966248e-07,
2430
+ "loss": 0.0,
2431
+ "step": 346
2432
+ },
2433
+ {
2434
+ "epoch": 4.819444444444445,
2435
+ "grad_norm": 0.00038043910171836615,
2436
+ "learning_rate": 7.66003060770498e-07,
2437
+ "loss": 0.0,
2438
+ "step": 347
2439
+ },
2440
+ {
2441
+ "epoch": 4.833333333333333,
2442
+ "grad_norm": 0.00027849708567373455,
2443
+ "learning_rate": 7.490396628216237e-07,
2444
+ "loss": 0.0,
2445
+ "step": 348
2446
+ },
2447
+ {
2448
+ "epoch": 4.847222222222222,
2449
+ "grad_norm": 0.00026442529633641243,
2450
+ "learning_rate": 7.322330470336314e-07,
2451
+ "loss": 0.0,
2452
+ "step": 349
2453
+ },
2454
+ {
2455
+ "epoch": 4.861111111111111,
2456
+ "grad_norm": 0.0002640223829075694,
2457
+ "learning_rate": 7.155847182821524e-07,
2458
+ "loss": 0.0,
2459
+ "step": 350
2460
+ },
2461
+ {
2462
+ "epoch": 4.875,
2463
+ "grad_norm": 0.0002679000608623028,
2464
+ "learning_rate": 6.990961672696908e-07,
2465
+ "loss": 0.0,
2466
+ "step": 351
2467
+ },
2468
+ {
2469
+ "epoch": 4.888888888888889,
2470
+ "grad_norm": 0.0003060480812564492,
2471
+ "learning_rate": 6.827688703921407e-07,
2472
+ "loss": 0.0,
2473
+ "step": 352
2474
+ },
2475
+ {
2476
+ "epoch": 4.902777777777778,
2477
+ "grad_norm": 0.0002725216909311712,
2478
+ "learning_rate": 6.666042896065983e-07,
2479
+ "loss": 0.0,
2480
+ "step": 353
2481
+ },
2482
+ {
2483
+ "epoch": 4.916666666666667,
2484
+ "grad_norm": 0.0007128149154596031,
2485
+ "learning_rate": 6.506038723004484e-07,
2486
+ "loss": 0.0,
2487
+ "step": 354
2488
+ },
2489
+ {
2490
+ "epoch": 4.930555555555555,
2491
+ "grad_norm": 0.0003282964462414384,
2492
+ "learning_rate": 6.347690511617693e-07,
2493
+ "loss": 0.0,
2494
+ "step": 355
2495
+ },
2496
+ {
2497
+ "epoch": 4.944444444444445,
2498
+ "grad_norm": 0.00026580950361676514,
2499
+ "learning_rate": 6.191012440510469e-07,
2500
+ "loss": 0.0,
2501
+ "step": 356
2502
+ },
2503
+ {
2504
+ "epoch": 4.958333333333333,
2505
+ "grad_norm": 0.0002644002088345587,
2506
+ "learning_rate": 6.036018538742208e-07,
2507
+ "loss": 0.0,
2508
+ "step": 357
2509
+ },
2510
+ {
2511
+ "epoch": 4.972222222222222,
2512
+ "grad_norm": 0.0002604973560664803,
2513
+ "learning_rate": 5.882722684570638e-07,
2514
+ "loss": 0.0,
2515
+ "step": 358
2516
+ },
2517
+ {
2518
+ "epoch": 4.986111111111111,
2519
+ "grad_norm": 0.0002634973789099604,
2520
+ "learning_rate": 5.731138604209169e-07,
2521
+ "loss": 0.0,
2522
+ "step": 359
2523
+ },
2524
+ {
2525
+ "epoch": 5.0,
2526
+ "grad_norm": 0.00026600516866892576,
2527
+ "learning_rate": 5.581279870597866e-07,
2528
+ "loss": 0.0,
2529
+ "step": 360
2530
+ }
2531
+ ],
2532
+ "logging_steps": 1,
2533
+ "max_steps": 432,
2534
+ "num_input_tokens_seen": 0,
2535
+ "num_train_epochs": 6,
2536
+ "save_steps": 72,
2537
+ "stateful_callbacks": {
2538
+ "TrainerControl": {
2539
+ "args": {
2540
+ "should_epoch_stop": false,
2541
+ "should_evaluate": false,
2542
+ "should_log": false,
2543
+ "should_save": true,
2544
+ "should_training_stop": false
2545
+ },
2546
+ "attributes": {}
2547
+ }
2548
+ },
2549
+ "total_flos": 9.064261680208282e+17,
2550
+ "train_batch_size": 4,
2551
+ "trial_name": null,
2552
+ "trial_params": null
2553
+ }
checkpoint-360/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c4a21cce8e23b70f0a541e7503c799ab823dd5a615b154bf086ba44af0edeef6
3
+ size 7992
checkpoint-360/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)
checkpoint-432/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: meta-llama/Llama-3.1-8B-Instruct
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.14.0
checkpoint-432/adapter_config.json ADDED
@@ -0,0 +1,40 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "meta-llama/Llama-3.1-8B-Instruct",
5
+ "bias": "none",
6
+ "eva_config": null,
7
+ "exclude_modules": null,
8
+ "fan_in_fan_out": null,
9
+ "inference_mode": true,
10
+ "init_lora_weights": true,
11
+ "layer_replication": null,
12
+ "layers_pattern": null,
13
+ "layers_to_transform": null,
14
+ "loftq_config": {},
15
+ "lora_alpha": 512,
16
+ "lora_bias": false,
17
+ "lora_dropout": 0.05,
18
+ "megatron_config": null,
19
+ "megatron_core": "megatron.core",
20
+ "modules_to_save": [
21
+ "embed_tokens",
22
+ "lm_head"
23
+ ],
24
+ "peft_type": "LORA",
25
+ "r": 256,
26
+ "rank_pattern": {},
27
+ "revision": null,
28
+ "target_modules": [
29
+ "o_proj",
30
+ "gate_proj",
31
+ "up_proj",
32
+ "q_proj",
33
+ "k_proj",
34
+ "down_proj",
35
+ "v_proj"
36
+ ],
37
+ "task_type": "CAUSAL_LM",
38
+ "use_dora": false,
39
+ "use_rslora": false
40
+ }
checkpoint-432/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f3f83e1c7b18523e50c33645a557501eb084d15f1f696abb2cf911bb7c9306dc
3
+ size 3443586272
checkpoint-432/global_step432/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:23f35894b1fa4d1fc99cb97412e754c3fa7d0a60c8ad46443146718bce642d1e
3
+ size 20661195036
checkpoint-432/global_step432/mp_rank_00_model_states.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:2535e5ed60212f54c48bb85b57e68e56e404144e133d1d15f4c4808332fef2e0
3
+ size 3555326649
checkpoint-432/latest ADDED
@@ -0,0 +1 @@
 
 
1
+ global_step432
checkpoint-432/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:3874c21ed51e73c9352fe3a4297172900da4aa49fa8a599cd59e19d567f13d7b
3
+ size 14244
checkpoint-432/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:111ca90245be96ef90c53bd1dd14d193f8b0438ebf2268676c1e7ceb5e4eb4c1
3
+ size 1064
checkpoint-432/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": "<|end_of_text|>",
18
+ "lstrip": false,
19
+ "normalized": false,
20
+ "rstrip": false,
21
+ "single_word": false
22
+ }
23
+ }
checkpoint-432/tokenizer.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6b9e4e7fb171f92fd137b777cc2714bf87d11576700a1dcd7a399e7bbe39537b
3
+ size 17209920
checkpoint-432/tokenizer_config.json ADDED
@@ -0,0 +1,2064 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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": "<|finetune_right_pad_id|>",
37
+ "lstrip": false,
38
+ "normalized": false,
39
+ "rstrip": false,
40
+ "single_word": false,
41
+ "special": true
42
+ },
43
+ "128005": {
44
+ "content": "<|reserved_special_token_2|>",
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": "<|eom_id|>",
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": "<|python_tag|>",
85
+ "lstrip": false,
86
+ "normalized": false,
87
+ "rstrip": false,
88
+ "single_word": false,
89
+ "special": true
90
+ },
91
+ "128011": {
92
+ "content": "<|reserved_special_token_3|>",
93
+ "lstrip": false,
94
+ "normalized": false,
95
+ "rstrip": false,
96
+ "single_word": false,
97
+ "special": true
98
+ },
99
+ "128012": {
100
+ "content": "<|reserved_special_token_4|>",
101
+ "lstrip": false,
102
+ "normalized": false,
103
+ "rstrip": false,
104
+ "single_word": false,
105
+ "special": true
106
+ },
107
+ "128013": {
108
+ "content": "<|reserved_special_token_5|>",
109
+ "lstrip": false,
110
+ "normalized": false,
111
+ "rstrip": false,
112
+ "single_word": false,
113
+ "special": true
114
+ },
115
+ "128014": {
116
+ "content": "<|reserved_special_token_6|>",
117
+ "lstrip": false,
118
+ "normalized": false,
119
+ "rstrip": false,
120
+ "single_word": false,
121
+ "special": true
122
+ },
123
+ "128015": {
124
+ "content": "<|reserved_special_token_7|>",
125
+ "lstrip": false,
126
+ "normalized": false,
127
+ "rstrip": false,
128
+ "single_word": false,
129
+ "special": true
130
+ },
131
+ "128016": {
132
+ "content": "<|reserved_special_token_8|>",
133
+ "lstrip": false,
134
+ "normalized": false,
135
+ "rstrip": false,
136
+ "single_word": false,
137
+ "special": true
138
+ },
139
+ "128017": {
140
+ "content": "<|reserved_special_token_9|>",
141
+ "lstrip": false,
142
+ "normalized": false,
143
+ "rstrip": false,
144
+ "single_word": false,
145
+ "special": true
146
+ },
147
+ "128018": {
148
+ "content": "<|reserved_special_token_10|>",
149
+ "lstrip": false,
150
+ "normalized": false,
151
+ "rstrip": false,
152
+ "single_word": false,
153
+ "special": true
154
+ },
155
+ "128019": {
156
+ "content": "<|reserved_special_token_11|>",
157
+ "lstrip": false,
158
+ "normalized": false,
159
+ "rstrip": false,
160
+ "single_word": false,
161
+ "special": true
162
+ },
163
+ "128020": {
164
+ "content": "<|reserved_special_token_12|>",
165
+ "lstrip": false,
166
+ "normalized": false,
167
+ "rstrip": false,
168
+ "single_word": false,
169
+ "special": true
170
+ },
171
+ "128021": {
172
+ "content": "<|reserved_special_token_13|>",
173
+ "lstrip": false,
174
+ "normalized": false,
175
+ "rstrip": false,
176
+ "single_word": false,
177
+ "special": true
178
+ },
179
+ "128022": {
180
+ "content": "<|reserved_special_token_14|>",
181
+ "lstrip": false,
182
+ "normalized": false,
183
+ "rstrip": false,
184
+ "single_word": false,
185
+ "special": true
186
+ },
187
+ "128023": {
188
+ "content": "<|reserved_special_token_15|>",
189
+ "lstrip": false,
190
+ "normalized": false,
191
+ "rstrip": false,
192
+ "single_word": false,
193
+ "special": true
194
+ },
195
+ "128024": {
196
+ "content": "<|reserved_special_token_16|>",
197
+ "lstrip": false,
198
+ "normalized": false,
199
+ "rstrip": false,
200
+ "single_word": false,
201
+ "special": true
202
+ },
203
+ "128025": {
204
+ "content": "<|reserved_special_token_17|>",
205
+ "lstrip": false,
206
+ "normalized": false,
207
+ "rstrip": false,
208
+ "single_word": false,
209
+ "special": true
210
+ },
211
+ "128026": {
212
+ "content": "<|reserved_special_token_18|>",
213
+ "lstrip": false,
214
+ "normalized": false,
215
+ "rstrip": false,
216
+ "single_word": false,
217
+ "special": true
218
+ },
219
+ "128027": {
220
+ "content": "<|reserved_special_token_19|>",
221
+ "lstrip": false,
222
+ "normalized": false,
223
+ "rstrip": false,
224
+ "single_word": false,
225
+ "special": true
226
+ },
227
+ "128028": {
228
+ "content": "<|reserved_special_token_20|>",
229
+ "lstrip": false,
230
+ "normalized": false,
231
+ "rstrip": false,
232
+ "single_word": false,
233
+ "special": true
234
+ },
235
+ "128029": {
236
+ "content": "<|reserved_special_token_21|>",
237
+ "lstrip": false,
238
+ "normalized": false,
239
+ "rstrip": false,
240
+ "single_word": false,
241
+ "special": true
242
+ },
243
+ "128030": {
244
+ "content": "<|reserved_special_token_22|>",
245
+ "lstrip": false,
246
+ "normalized": false,
247
+ "rstrip": false,
248
+ "single_word": false,
249
+ "special": true
250
+ },
251
+ "128031": {
252
+ "content": "<|reserved_special_token_23|>",
253
+ "lstrip": false,
254
+ "normalized": false,
255
+ "rstrip": false,
256
+ "single_word": false,
257
+ "special": true
258
+ },
259
+ "128032": {
260
+ "content": "<|reserved_special_token_24|>",
261
+ "lstrip": false,
262
+ "normalized": false,
263
+ "rstrip": false,
264
+ "single_word": false,
265
+ "special": true
266
+ },
267
+ "128033": {
268
+ "content": "<|reserved_special_token_25|>",
269
+ "lstrip": false,
270
+ "normalized": false,
271
+ "rstrip": false,
272
+ "single_word": false,
273
+ "special": true
274
+ },
275
+ "128034": {
276
+ "content": "<|reserved_special_token_26|>",
277
+ "lstrip": false,
278
+ "normalized": false,
279
+ "rstrip": false,
280
+ "single_word": false,
281
+ "special": true
282
+ },
283
+ "128035": {
284
+ "content": "<|reserved_special_token_27|>",
285
+ "lstrip": false,
286
+ "normalized": false,
287
+ "rstrip": false,
288
+ "single_word": false,
289
+ "special": true
290
+ },
291
+ "128036": {
292
+ "content": "<|reserved_special_token_28|>",
293
+ "lstrip": false,
294
+ "normalized": false,
295
+ "rstrip": false,
296
+ "single_word": false,
297
+ "special": true
298
+ },
299
+ "128037": {
300
+ "content": "<|reserved_special_token_29|>",
301
+ "lstrip": false,
302
+ "normalized": false,
303
+ "rstrip": false,
304
+ "single_word": false,
305
+ "special": true
306
+ },
307
+ "128038": {
308
+ "content": "<|reserved_special_token_30|>",
309
+ "lstrip": false,
310
+ "normalized": false,
311
+ "rstrip": false,
312
+ "single_word": false,
313
+ "special": true
314
+ },
315
+ "128039": {
316
+ "content": "<|reserved_special_token_31|>",
317
+ "lstrip": false,
318
+ "normalized": false,
319
+ "rstrip": false,
320
+ "single_word": false,
321
+ "special": true
322
+ },
323
+ "128040": {
324
+ "content": "<|reserved_special_token_32|>",
325
+ "lstrip": false,
326
+ "normalized": false,
327
+ "rstrip": false,
328
+ "single_word": false,
329
+ "special": true
330
+ },
331
+ "128041": {
332
+ "content": "<|reserved_special_token_33|>",
333
+ "lstrip": false,
334
+ "normalized": false,
335
+ "rstrip": false,
336
+ "single_word": false,
337
+ "special": true
338
+ },
339
+ "128042": {
340
+ "content": "<|reserved_special_token_34|>",
341
+ "lstrip": false,
342
+ "normalized": false,
343
+ "rstrip": false,
344
+ "single_word": false,
345
+ "special": true
346
+ },
347
+ "128043": {
348
+ "content": "<|reserved_special_token_35|>",
349
+ "lstrip": false,
350
+ "normalized": false,
351
+ "rstrip": false,
352
+ "single_word": false,
353
+ "special": true
354
+ },
355
+ "128044": {
356
+ "content": "<|reserved_special_token_36|>",
357
+ "lstrip": false,
358
+ "normalized": false,
359
+ "rstrip": false,
360
+ "single_word": false,
361
+ "special": true
362
+ },
363
+ "128045": {
364
+ "content": "<|reserved_special_token_37|>",
365
+ "lstrip": false,
366
+ "normalized": false,
367
+ "rstrip": false,
368
+ "single_word": false,
369
+ "special": true
370
+ },
371
+ "128046": {
372
+ "content": "<|reserved_special_token_38|>",
373
+ "lstrip": false,
374
+ "normalized": false,
375
+ "rstrip": false,
376
+ "single_word": false,
377
+ "special": true
378
+ },
379
+ "128047": {
380
+ "content": "<|reserved_special_token_39|>",
381
+ "lstrip": false,
382
+ "normalized": false,
383
+ "rstrip": false,
384
+ "single_word": false,
385
+ "special": true
386
+ },
387
+ "128048": {
388
+ "content": "<|reserved_special_token_40|>",
389
+ "lstrip": false,
390
+ "normalized": false,
391
+ "rstrip": false,
392
+ "single_word": false,
393
+ "special": true
394
+ },
395
+ "128049": {
396
+ "content": "<|reserved_special_token_41|>",
397
+ "lstrip": false,
398
+ "normalized": false,
399
+ "rstrip": false,
400
+ "single_word": false,
401
+ "special": true
402
+ },
403
+ "128050": {
404
+ "content": "<|reserved_special_token_42|>",
405
+ "lstrip": false,
406
+ "normalized": false,
407
+ "rstrip": false,
408
+ "single_word": false,
409
+ "special": true
410
+ },
411
+ "128051": {
412
+ "content": "<|reserved_special_token_43|>",
413
+ "lstrip": false,
414
+ "normalized": false,
415
+ "rstrip": false,
416
+ "single_word": false,
417
+ "special": true
418
+ },
419
+ "128052": {
420
+ "content": "<|reserved_special_token_44|>",
421
+ "lstrip": false,
422
+ "normalized": false,
423
+ "rstrip": false,
424
+ "single_word": false,
425
+ "special": true
426
+ },
427
+ "128053": {
428
+ "content": "<|reserved_special_token_45|>",
429
+ "lstrip": false,
430
+ "normalized": false,
431
+ "rstrip": false,
432
+ "single_word": false,
433
+ "special": true
434
+ },
435
+ "128054": {
436
+ "content": "<|reserved_special_token_46|>",
437
+ "lstrip": false,
438
+ "normalized": false,
439
+ "rstrip": false,
440
+ "single_word": false,
441
+ "special": true
442
+ },
443
+ "128055": {
444
+ "content": "<|reserved_special_token_47|>",
445
+ "lstrip": false,
446
+ "normalized": false,
447
+ "rstrip": false,
448
+ "single_word": false,
449
+ "special": true
450
+ },
451
+ "128056": {
452
+ "content": "<|reserved_special_token_48|>",
453
+ "lstrip": false,
454
+ "normalized": false,
455
+ "rstrip": false,
456
+ "single_word": false,
457
+ "special": true
458
+ },
459
+ "128057": {
460
+ "content": "<|reserved_special_token_49|>",
461
+ "lstrip": false,
462
+ "normalized": false,
463
+ "rstrip": false,
464
+ "single_word": false,
465
+ "special": true
466
+ },
467
+ "128058": {
468
+ "content": "<|reserved_special_token_50|>",
469
+ "lstrip": false,
470
+ "normalized": false,
471
+ "rstrip": false,
472
+ "single_word": false,
473
+ "special": true
474
+ },
475
+ "128059": {
476
+ "content": "<|reserved_special_token_51|>",
477
+ "lstrip": false,
478
+ "normalized": false,
479
+ "rstrip": false,
480
+ "single_word": false,
481
+ "special": true
482
+ },
483
+ "128060": {
484
+ "content": "<|reserved_special_token_52|>",
485
+ "lstrip": false,
486
+ "normalized": false,
487
+ "rstrip": false,
488
+ "single_word": false,
489
+ "special": true
490
+ },
491
+ "128061": {
492
+ "content": "<|reserved_special_token_53|>",
493
+ "lstrip": false,
494
+ "normalized": false,
495
+ "rstrip": false,
496
+ "single_word": false,
497
+ "special": true
498
+ },
499
+ "128062": {
500
+ "content": "<|reserved_special_token_54|>",
501
+ "lstrip": false,
502
+ "normalized": false,
503
+ "rstrip": false,
504
+ "single_word": false,
505
+ "special": true
506
+ },
507
+ "128063": {
508
+ "content": "<|reserved_special_token_55|>",
509
+ "lstrip": false,
510
+ "normalized": false,
511
+ "rstrip": false,
512
+ "single_word": false,
513
+ "special": true
514
+ },
515
+ "128064": {
516
+ "content": "<|reserved_special_token_56|>",
517
+ "lstrip": false,
518
+ "normalized": false,
519
+ "rstrip": false,
520
+ "single_word": false,
521
+ "special": true
522
+ },
523
+ "128065": {
524
+ "content": "<|reserved_special_token_57|>",
525
+ "lstrip": false,
526
+ "normalized": false,
527
+ "rstrip": false,
528
+ "single_word": false,
529
+ "special": true
530
+ },
531
+ "128066": {
532
+ "content": "<|reserved_special_token_58|>",
533
+ "lstrip": false,
534
+ "normalized": false,
535
+ "rstrip": false,
536
+ "single_word": false,
537
+ "special": true
538
+ },
539
+ "128067": {
540
+ "content": "<|reserved_special_token_59|>",
541
+ "lstrip": false,
542
+ "normalized": false,
543
+ "rstrip": false,
544
+ "single_word": false,
545
+ "special": true
546
+ },
547
+ "128068": {
548
+ "content": "<|reserved_special_token_60|>",
549
+ "lstrip": false,
550
+ "normalized": false,
551
+ "rstrip": false,
552
+ "single_word": false,
553
+ "special": true
554
+ },
555
+ "128069": {
556
+ "content": "<|reserved_special_token_61|>",
557
+ "lstrip": false,
558
+ "normalized": false,
559
+ "rstrip": false,
560
+ "single_word": false,
561
+ "special": true
562
+ },
563
+ "128070": {
564
+ "content": "<|reserved_special_token_62|>",
565
+ "lstrip": false,
566
+ "normalized": false,
567
+ "rstrip": false,
568
+ "single_word": false,
569
+ "special": true
570
+ },
571
+ "128071": {
572
+ "content": "<|reserved_special_token_63|>",
573
+ "lstrip": false,
574
+ "normalized": false,
575
+ "rstrip": false,
576
+ "single_word": false,
577
+ "special": true
578
+ },
579
+ "128072": {
580
+ "content": "<|reserved_special_token_64|>",
581
+ "lstrip": false,
582
+ "normalized": false,
583
+ "rstrip": false,
584
+ "single_word": false,
585
+ "special": true
586
+ },
587
+ "128073": {
588
+ "content": "<|reserved_special_token_65|>",
589
+ "lstrip": false,
590
+ "normalized": false,
591
+ "rstrip": false,
592
+ "single_word": false,
593
+ "special": true
594
+ },
595
+ "128074": {
596
+ "content": "<|reserved_special_token_66|>",
597
+ "lstrip": false,
598
+ "normalized": false,
599
+ "rstrip": false,
600
+ "single_word": false,
601
+ "special": true
602
+ },
603
+ "128075": {
604
+ "content": "<|reserved_special_token_67|>",
605
+ "lstrip": false,
606
+ "normalized": false,
607
+ "rstrip": false,
608
+ "single_word": false,
609
+ "special": true
610
+ },
611
+ "128076": {
612
+ "content": "<|reserved_special_token_68|>",
613
+ "lstrip": false,
614
+ "normalized": false,
615
+ "rstrip": false,
616
+ "single_word": false,
617
+ "special": true
618
+ },
619
+ "128077": {
620
+ "content": "<|reserved_special_token_69|>",
621
+ "lstrip": false,
622
+ "normalized": false,
623
+ "rstrip": false,
624
+ "single_word": false,
625
+ "special": true
626
+ },
627
+ "128078": {
628
+ "content": "<|reserved_special_token_70|>",
629
+ "lstrip": false,
630
+ "normalized": false,
631
+ "rstrip": false,
632
+ "single_word": false,
633
+ "special": true
634
+ },
635
+ "128079": {
636
+ "content": "<|reserved_special_token_71|>",
637
+ "lstrip": false,
638
+ "normalized": false,
639
+ "rstrip": false,
640
+ "single_word": false,
641
+ "special": true
642
+ },
643
+ "128080": {
644
+ "content": "<|reserved_special_token_72|>",
645
+ "lstrip": false,
646
+ "normalized": false,
647
+ "rstrip": false,
648
+ "single_word": false,
649
+ "special": true
650
+ },
651
+ "128081": {
652
+ "content": "<|reserved_special_token_73|>",
653
+ "lstrip": false,
654
+ "normalized": false,
655
+ "rstrip": false,
656
+ "single_word": false,
657
+ "special": true
658
+ },
659
+ "128082": {
660
+ "content": "<|reserved_special_token_74|>",
661
+ "lstrip": false,
662
+ "normalized": false,
663
+ "rstrip": false,
664
+ "single_word": false,
665
+ "special": true
666
+ },
667
+ "128083": {
668
+ "content": "<|reserved_special_token_75|>",
669
+ "lstrip": false,
670
+ "normalized": false,
671
+ "rstrip": false,
672
+ "single_word": false,
673
+ "special": true
674
+ },
675
+ "128084": {
676
+ "content": "<|reserved_special_token_76|>",
677
+ "lstrip": false,
678
+ "normalized": false,
679
+ "rstrip": false,
680
+ "single_word": false,
681
+ "special": true
682
+ },
683
+ "128085": {
684
+ "content": "<|reserved_special_token_77|>",
685
+ "lstrip": false,
686
+ "normalized": false,
687
+ "rstrip": false,
688
+ "single_word": false,
689
+ "special": true
690
+ },
691
+ "128086": {
692
+ "content": "<|reserved_special_token_78|>",
693
+ "lstrip": false,
694
+ "normalized": false,
695
+ "rstrip": false,
696
+ "single_word": false,
697
+ "special": true
698
+ },
699
+ "128087": {
700
+ "content": "<|reserved_special_token_79|>",
701
+ "lstrip": false,
702
+ "normalized": false,
703
+ "rstrip": false,
704
+ "single_word": false,
705
+ "special": true
706
+ },
707
+ "128088": {
708
+ "content": "<|reserved_special_token_80|>",
709
+ "lstrip": false,
710
+ "normalized": false,
711
+ "rstrip": false,
712
+ "single_word": false,
713
+ "special": true
714
+ },
715
+ "128089": {
716
+ "content": "<|reserved_special_token_81|>",
717
+ "lstrip": false,
718
+ "normalized": false,
719
+ "rstrip": false,
720
+ "single_word": false,
721
+ "special": true
722
+ },
723
+ "128090": {
724
+ "content": "<|reserved_special_token_82|>",
725
+ "lstrip": false,
726
+ "normalized": false,
727
+ "rstrip": false,
728
+ "single_word": false,
729
+ "special": true
730
+ },
731
+ "128091": {
732
+ "content": "<|reserved_special_token_83|>",
733
+ "lstrip": false,
734
+ "normalized": false,
735
+ "rstrip": false,
736
+ "single_word": false,
737
+ "special": true
738
+ },
739
+ "128092": {
740
+ "content": "<|reserved_special_token_84|>",
741
+ "lstrip": false,
742
+ "normalized": false,
743
+ "rstrip": false,
744
+ "single_word": false,
745
+ "special": true
746
+ },
747
+ "128093": {
748
+ "content": "<|reserved_special_token_85|>",
749
+ "lstrip": false,
750
+ "normalized": false,
751
+ "rstrip": false,
752
+ "single_word": false,
753
+ "special": true
754
+ },
755
+ "128094": {
756
+ "content": "<|reserved_special_token_86|>",
757
+ "lstrip": false,
758
+ "normalized": false,
759
+ "rstrip": false,
760
+ "single_word": false,
761
+ "special": true
762
+ },
763
+ "128095": {
764
+ "content": "<|reserved_special_token_87|>",
765
+ "lstrip": false,
766
+ "normalized": false,
767
+ "rstrip": false,
768
+ "single_word": false,
769
+ "special": true
770
+ },
771
+ "128096": {
772
+ "content": "<|reserved_special_token_88|>",
773
+ "lstrip": false,
774
+ "normalized": false,
775
+ "rstrip": false,
776
+ "single_word": false,
777
+ "special": true
778
+ },
779
+ "128097": {
780
+ "content": "<|reserved_special_token_89|>",
781
+ "lstrip": false,
782
+ "normalized": false,
783
+ "rstrip": false,
784
+ "single_word": false,
785
+ "special": true
786
+ },
787
+ "128098": {
788
+ "content": "<|reserved_special_token_90|>",
789
+ "lstrip": false,
790
+ "normalized": false,
791
+ "rstrip": false,
792
+ "single_word": false,
793
+ "special": true
794
+ },
795
+ "128099": {
796
+ "content": "<|reserved_special_token_91|>",
797
+ "lstrip": false,
798
+ "normalized": false,
799
+ "rstrip": false,
800
+ "single_word": false,
801
+ "special": true
802
+ },
803
+ "128100": {
804
+ "content": "<|reserved_special_token_92|>",
805
+ "lstrip": false,
806
+ "normalized": false,
807
+ "rstrip": false,
808
+ "single_word": false,
809
+ "special": true
810
+ },
811
+ "128101": {
812
+ "content": "<|reserved_special_token_93|>",
813
+ "lstrip": false,
814
+ "normalized": false,
815
+ "rstrip": false,
816
+ "single_word": false,
817
+ "special": true
818
+ },
819
+ "128102": {
820
+ "content": "<|reserved_special_token_94|>",
821
+ "lstrip": false,
822
+ "normalized": false,
823
+ "rstrip": false,
824
+ "single_word": false,
825
+ "special": true
826
+ },
827
+ "128103": {
828
+ "content": "<|reserved_special_token_95|>",
829
+ "lstrip": false,
830
+ "normalized": false,
831
+ "rstrip": false,
832
+ "single_word": false,
833
+ "special": true
834
+ },
835
+ "128104": {
836
+ "content": "<|reserved_special_token_96|>",
837
+ "lstrip": false,
838
+ "normalized": false,
839
+ "rstrip": false,
840
+ "single_word": false,
841
+ "special": true
842
+ },
843
+ "128105": {
844
+ "content": "<|reserved_special_token_97|>",
845
+ "lstrip": false,
846
+ "normalized": false,
847
+ "rstrip": false,
848
+ "single_word": false,
849
+ "special": true
850
+ },
851
+ "128106": {
852
+ "content": "<|reserved_special_token_98|>",
853
+ "lstrip": false,
854
+ "normalized": false,
855
+ "rstrip": false,
856
+ "single_word": false,
857
+ "special": true
858
+ },
859
+ "128107": {
860
+ "content": "<|reserved_special_token_99|>",
861
+ "lstrip": false,
862
+ "normalized": false,
863
+ "rstrip": false,
864
+ "single_word": false,
865
+ "special": true
866
+ },
867
+ "128108": {
868
+ "content": "<|reserved_special_token_100|>",
869
+ "lstrip": false,
870
+ "normalized": false,
871
+ "rstrip": false,
872
+ "single_word": false,
873
+ "special": true
874
+ },
875
+ "128109": {
876
+ "content": "<|reserved_special_token_101|>",
877
+ "lstrip": false,
878
+ "normalized": false,
879
+ "rstrip": false,
880
+ "single_word": false,
881
+ "special": true
882
+ },
883
+ "128110": {
884
+ "content": "<|reserved_special_token_102|>",
885
+ "lstrip": false,
886
+ "normalized": false,
887
+ "rstrip": false,
888
+ "single_word": false,
889
+ "special": true
890
+ },
891
+ "128111": {
892
+ "content": "<|reserved_special_token_103|>",
893
+ "lstrip": false,
894
+ "normalized": false,
895
+ "rstrip": false,
896
+ "single_word": false,
897
+ "special": true
898
+ },
899
+ "128112": {
900
+ "content": "<|reserved_special_token_104|>",
901
+ "lstrip": false,
902
+ "normalized": false,
903
+ "rstrip": false,
904
+ "single_word": false,
905
+ "special": true
906
+ },
907
+ "128113": {
908
+ "content": "<|reserved_special_token_105|>",
909
+ "lstrip": false,
910
+ "normalized": false,
911
+ "rstrip": false,
912
+ "single_word": false,
913
+ "special": true
914
+ },
915
+ "128114": {
916
+ "content": "<|reserved_special_token_106|>",
917
+ "lstrip": false,
918
+ "normalized": false,
919
+ "rstrip": false,
920
+ "single_word": false,
921
+ "special": true
922
+ },
923
+ "128115": {
924
+ "content": "<|reserved_special_token_107|>",
925
+ "lstrip": false,
926
+ "normalized": false,
927
+ "rstrip": false,
928
+ "single_word": false,
929
+ "special": true
930
+ },
931
+ "128116": {
932
+ "content": "<|reserved_special_token_108|>",
933
+ "lstrip": false,
934
+ "normalized": false,
935
+ "rstrip": false,
936
+ "single_word": false,
937
+ "special": true
938
+ },
939
+ "128117": {
940
+ "content": "<|reserved_special_token_109|>",
941
+ "lstrip": false,
942
+ "normalized": false,
943
+ "rstrip": false,
944
+ "single_word": false,
945
+ "special": true
946
+ },
947
+ "128118": {
948
+ "content": "<|reserved_special_token_110|>",
949
+ "lstrip": false,
950
+ "normalized": false,
951
+ "rstrip": false,
952
+ "single_word": false,
953
+ "special": true
954
+ },
955
+ "128119": {
956
+ "content": "<|reserved_special_token_111|>",
957
+ "lstrip": false,
958
+ "normalized": false,
959
+ "rstrip": false,
960
+ "single_word": false,
961
+ "special": true
962
+ },
963
+ "128120": {
964
+ "content": "<|reserved_special_token_112|>",
965
+ "lstrip": false,
966
+ "normalized": false,
967
+ "rstrip": false,
968
+ "single_word": false,
969
+ "special": true
970
+ },
971
+ "128121": {
972
+ "content": "<|reserved_special_token_113|>",
973
+ "lstrip": false,
974
+ "normalized": false,
975
+ "rstrip": false,
976
+ "single_word": false,
977
+ "special": true
978
+ },
979
+ "128122": {
980
+ "content": "<|reserved_special_token_114|>",
981
+ "lstrip": false,
982
+ "normalized": false,
983
+ "rstrip": false,
984
+ "single_word": false,
985
+ "special": true
986
+ },
987
+ "128123": {
988
+ "content": "<|reserved_special_token_115|>",
989
+ "lstrip": false,
990
+ "normalized": false,
991
+ "rstrip": false,
992
+ "single_word": false,
993
+ "special": true
994
+ },
995
+ "128124": {
996
+ "content": "<|reserved_special_token_116|>",
997
+ "lstrip": false,
998
+ "normalized": false,
999
+ "rstrip": false,
1000
+ "single_word": false,
1001
+ "special": true
1002
+ },
1003
+ "128125": {
1004
+ "content": "<|reserved_special_token_117|>",
1005
+ "lstrip": false,
1006
+ "normalized": false,
1007
+ "rstrip": false,
1008
+ "single_word": false,
1009
+ "special": true
1010
+ },
1011
+ "128126": {
1012
+ "content": "<|reserved_special_token_118|>",
1013
+ "lstrip": false,
1014
+ "normalized": false,
1015
+ "rstrip": false,
1016
+ "single_word": false,
1017
+ "special": true
1018
+ },
1019
+ "128127": {
1020
+ "content": "<|reserved_special_token_119|>",
1021
+ "lstrip": false,
1022
+ "normalized": false,
1023
+ "rstrip": false,
1024
+ "single_word": false,
1025
+ "special": true
1026
+ },
1027
+ "128128": {
1028
+ "content": "<|reserved_special_token_120|>",
1029
+ "lstrip": false,
1030
+ "normalized": false,
1031
+ "rstrip": false,
1032
+ "single_word": false,
1033
+ "special": true
1034
+ },
1035
+ "128129": {
1036
+ "content": "<|reserved_special_token_121|>",
1037
+ "lstrip": false,
1038
+ "normalized": false,
1039
+ "rstrip": false,
1040
+ "single_word": false,
1041
+ "special": true
1042
+ },
1043
+ "128130": {
1044
+ "content": "<|reserved_special_token_122|>",
1045
+ "lstrip": false,
1046
+ "normalized": false,
1047
+ "rstrip": false,
1048
+ "single_word": false,
1049
+ "special": true
1050
+ },
1051
+ "128131": {
1052
+ "content": "<|reserved_special_token_123|>",
1053
+ "lstrip": false,
1054
+ "normalized": false,
1055
+ "rstrip": false,
1056
+ "single_word": false,
1057
+ "special": true
1058
+ },
1059
+ "128132": {
1060
+ "content": "<|reserved_special_token_124|>",
1061
+ "lstrip": false,
1062
+ "normalized": false,
1063
+ "rstrip": false,
1064
+ "single_word": false,
1065
+ "special": true
1066
+ },
1067
+ "128133": {
1068
+ "content": "<|reserved_special_token_125|>",
1069
+ "lstrip": false,
1070
+ "normalized": false,
1071
+ "rstrip": false,
1072
+ "single_word": false,
1073
+ "special": true
1074
+ },
1075
+ "128134": {
1076
+ "content": "<|reserved_special_token_126|>",
1077
+ "lstrip": false,
1078
+ "normalized": false,
1079
+ "rstrip": false,
1080
+ "single_word": false,
1081
+ "special": true
1082
+ },
1083
+ "128135": {
1084
+ "content": "<|reserved_special_token_127|>",
1085
+ "lstrip": false,
1086
+ "normalized": false,
1087
+ "rstrip": false,
1088
+ "single_word": false,
1089
+ "special": true
1090
+ },
1091
+ "128136": {
1092
+ "content": "<|reserved_special_token_128|>",
1093
+ "lstrip": false,
1094
+ "normalized": false,
1095
+ "rstrip": false,
1096
+ "single_word": false,
1097
+ "special": true
1098
+ },
1099
+ "128137": {
1100
+ "content": "<|reserved_special_token_129|>",
1101
+ "lstrip": false,
1102
+ "normalized": false,
1103
+ "rstrip": false,
1104
+ "single_word": false,
1105
+ "special": true
1106
+ },
1107
+ "128138": {
1108
+ "content": "<|reserved_special_token_130|>",
1109
+ "lstrip": false,
1110
+ "normalized": false,
1111
+ "rstrip": false,
1112
+ "single_word": false,
1113
+ "special": true
1114
+ },
1115
+ "128139": {
1116
+ "content": "<|reserved_special_token_131|>",
1117
+ "lstrip": false,
1118
+ "normalized": false,
1119
+ "rstrip": false,
1120
+ "single_word": false,
1121
+ "special": true
1122
+ },
1123
+ "128140": {
1124
+ "content": "<|reserved_special_token_132|>",
1125
+ "lstrip": false,
1126
+ "normalized": false,
1127
+ "rstrip": false,
1128
+ "single_word": false,
1129
+ "special": true
1130
+ },
1131
+ "128141": {
1132
+ "content": "<|reserved_special_token_133|>",
1133
+ "lstrip": false,
1134
+ "normalized": false,
1135
+ "rstrip": false,
1136
+ "single_word": false,
1137
+ "special": true
1138
+ },
1139
+ "128142": {
1140
+ "content": "<|reserved_special_token_134|>",
1141
+ "lstrip": false,
1142
+ "normalized": false,
1143
+ "rstrip": false,
1144
+ "single_word": false,
1145
+ "special": true
1146
+ },
1147
+ "128143": {
1148
+ "content": "<|reserved_special_token_135|>",
1149
+ "lstrip": false,
1150
+ "normalized": false,
1151
+ "rstrip": false,
1152
+ "single_word": false,
1153
+ "special": true
1154
+ },
1155
+ "128144": {
1156
+ "content": "<|reserved_special_token_136|>",
1157
+ "lstrip": false,
1158
+ "normalized": false,
1159
+ "rstrip": false,
1160
+ "single_word": false,
1161
+ "special": true
1162
+ },
1163
+ "128145": {
1164
+ "content": "<|reserved_special_token_137|>",
1165
+ "lstrip": false,
1166
+ "normalized": false,
1167
+ "rstrip": false,
1168
+ "single_word": false,
1169
+ "special": true
1170
+ },
1171
+ "128146": {
1172
+ "content": "<|reserved_special_token_138|>",
1173
+ "lstrip": false,
1174
+ "normalized": false,
1175
+ "rstrip": false,
1176
+ "single_word": false,
1177
+ "special": true
1178
+ },
1179
+ "128147": {
1180
+ "content": "<|reserved_special_token_139|>",
1181
+ "lstrip": false,
1182
+ "normalized": false,
1183
+ "rstrip": false,
1184
+ "single_word": false,
1185
+ "special": true
1186
+ },
1187
+ "128148": {
1188
+ "content": "<|reserved_special_token_140|>",
1189
+ "lstrip": false,
1190
+ "normalized": false,
1191
+ "rstrip": false,
1192
+ "single_word": false,
1193
+ "special": true
1194
+ },
1195
+ "128149": {
1196
+ "content": "<|reserved_special_token_141|>",
1197
+ "lstrip": false,
1198
+ "normalized": false,
1199
+ "rstrip": false,
1200
+ "single_word": false,
1201
+ "special": true
1202
+ },
1203
+ "128150": {
1204
+ "content": "<|reserved_special_token_142|>",
1205
+ "lstrip": false,
1206
+ "normalized": false,
1207
+ "rstrip": false,
1208
+ "single_word": false,
1209
+ "special": true
1210
+ },
1211
+ "128151": {
1212
+ "content": "<|reserved_special_token_143|>",
1213
+ "lstrip": false,
1214
+ "normalized": false,
1215
+ "rstrip": false,
1216
+ "single_word": false,
1217
+ "special": true
1218
+ },
1219
+ "128152": {
1220
+ "content": "<|reserved_special_token_144|>",
1221
+ "lstrip": false,
1222
+ "normalized": false,
1223
+ "rstrip": false,
1224
+ "single_word": false,
1225
+ "special": true
1226
+ },
1227
+ "128153": {
1228
+ "content": "<|reserved_special_token_145|>",
1229
+ "lstrip": false,
1230
+ "normalized": false,
1231
+ "rstrip": false,
1232
+ "single_word": false,
1233
+ "special": true
1234
+ },
1235
+ "128154": {
1236
+ "content": "<|reserved_special_token_146|>",
1237
+ "lstrip": false,
1238
+ "normalized": false,
1239
+ "rstrip": false,
1240
+ "single_word": false,
1241
+ "special": true
1242
+ },
1243
+ "128155": {
1244
+ "content": "<|reserved_special_token_147|>",
1245
+ "lstrip": false,
1246
+ "normalized": false,
1247
+ "rstrip": false,
1248
+ "single_word": false,
1249
+ "special": true
1250
+ },
1251
+ "128156": {
1252
+ "content": "<|reserved_special_token_148|>",
1253
+ "lstrip": false,
1254
+ "normalized": false,
1255
+ "rstrip": false,
1256
+ "single_word": false,
1257
+ "special": true
1258
+ },
1259
+ "128157": {
1260
+ "content": "<|reserved_special_token_149|>",
1261
+ "lstrip": false,
1262
+ "normalized": false,
1263
+ "rstrip": false,
1264
+ "single_word": false,
1265
+ "special": true
1266
+ },
1267
+ "128158": {
1268
+ "content": "<|reserved_special_token_150|>",
1269
+ "lstrip": false,
1270
+ "normalized": false,
1271
+ "rstrip": false,
1272
+ "single_word": false,
1273
+ "special": true
1274
+ },
1275
+ "128159": {
1276
+ "content": "<|reserved_special_token_151|>",
1277
+ "lstrip": false,
1278
+ "normalized": false,
1279
+ "rstrip": false,
1280
+ "single_word": false,
1281
+ "special": true
1282
+ },
1283
+ "128160": {
1284
+ "content": "<|reserved_special_token_152|>",
1285
+ "lstrip": false,
1286
+ "normalized": false,
1287
+ "rstrip": false,
1288
+ "single_word": false,
1289
+ "special": true
1290
+ },
1291
+ "128161": {
1292
+ "content": "<|reserved_special_token_153|>",
1293
+ "lstrip": false,
1294
+ "normalized": false,
1295
+ "rstrip": false,
1296
+ "single_word": false,
1297
+ "special": true
1298
+ },
1299
+ "128162": {
1300
+ "content": "<|reserved_special_token_154|>",
1301
+ "lstrip": false,
1302
+ "normalized": false,
1303
+ "rstrip": false,
1304
+ "single_word": false,
1305
+ "special": true
1306
+ },
1307
+ "128163": {
1308
+ "content": "<|reserved_special_token_155|>",
1309
+ "lstrip": false,
1310
+ "normalized": false,
1311
+ "rstrip": false,
1312
+ "single_word": false,
1313
+ "special": true
1314
+ },
1315
+ "128164": {
1316
+ "content": "<|reserved_special_token_156|>",
1317
+ "lstrip": false,
1318
+ "normalized": false,
1319
+ "rstrip": false,
1320
+ "single_word": false,
1321
+ "special": true
1322
+ },
1323
+ "128165": {
1324
+ "content": "<|reserved_special_token_157|>",
1325
+ "lstrip": false,
1326
+ "normalized": false,
1327
+ "rstrip": false,
1328
+ "single_word": false,
1329
+ "special": true
1330
+ },
1331
+ "128166": {
1332
+ "content": "<|reserved_special_token_158|>",
1333
+ "lstrip": false,
1334
+ "normalized": false,
1335
+ "rstrip": false,
1336
+ "single_word": false,
1337
+ "special": true
1338
+ },
1339
+ "128167": {
1340
+ "content": "<|reserved_special_token_159|>",
1341
+ "lstrip": false,
1342
+ "normalized": false,
1343
+ "rstrip": false,
1344
+ "single_word": false,
1345
+ "special": true
1346
+ },
1347
+ "128168": {
1348
+ "content": "<|reserved_special_token_160|>",
1349
+ "lstrip": false,
1350
+ "normalized": false,
1351
+ "rstrip": false,
1352
+ "single_word": false,
1353
+ "special": true
1354
+ },
1355
+ "128169": {
1356
+ "content": "<|reserved_special_token_161|>",
1357
+ "lstrip": false,
1358
+ "normalized": false,
1359
+ "rstrip": false,
1360
+ "single_word": false,
1361
+ "special": true
1362
+ },
1363
+ "128170": {
1364
+ "content": "<|reserved_special_token_162|>",
1365
+ "lstrip": false,
1366
+ "normalized": false,
1367
+ "rstrip": false,
1368
+ "single_word": false,
1369
+ "special": true
1370
+ },
1371
+ "128171": {
1372
+ "content": "<|reserved_special_token_163|>",
1373
+ "lstrip": false,
1374
+ "normalized": false,
1375
+ "rstrip": false,
1376
+ "single_word": false,
1377
+ "special": true
1378
+ },
1379
+ "128172": {
1380
+ "content": "<|reserved_special_token_164|>",
1381
+ "lstrip": false,
1382
+ "normalized": false,
1383
+ "rstrip": false,
1384
+ "single_word": false,
1385
+ "special": true
1386
+ },
1387
+ "128173": {
1388
+ "content": "<|reserved_special_token_165|>",
1389
+ "lstrip": false,
1390
+ "normalized": false,
1391
+ "rstrip": false,
1392
+ "single_word": false,
1393
+ "special": true
1394
+ },
1395
+ "128174": {
1396
+ "content": "<|reserved_special_token_166|>",
1397
+ "lstrip": false,
1398
+ "normalized": false,
1399
+ "rstrip": false,
1400
+ "single_word": false,
1401
+ "special": true
1402
+ },
1403
+ "128175": {
1404
+ "content": "<|reserved_special_token_167|>",
1405
+ "lstrip": false,
1406
+ "normalized": false,
1407
+ "rstrip": false,
1408
+ "single_word": false,
1409
+ "special": true
1410
+ },
1411
+ "128176": {
1412
+ "content": "<|reserved_special_token_168|>",
1413
+ "lstrip": false,
1414
+ "normalized": false,
1415
+ "rstrip": false,
1416
+ "single_word": false,
1417
+ "special": true
1418
+ },
1419
+ "128177": {
1420
+ "content": "<|reserved_special_token_169|>",
1421
+ "lstrip": false,
1422
+ "normalized": false,
1423
+ "rstrip": false,
1424
+ "single_word": false,
1425
+ "special": true
1426
+ },
1427
+ "128178": {
1428
+ "content": "<|reserved_special_token_170|>",
1429
+ "lstrip": false,
1430
+ "normalized": false,
1431
+ "rstrip": false,
1432
+ "single_word": false,
1433
+ "special": true
1434
+ },
1435
+ "128179": {
1436
+ "content": "<|reserved_special_token_171|>",
1437
+ "lstrip": false,
1438
+ "normalized": false,
1439
+ "rstrip": false,
1440
+ "single_word": false,
1441
+ "special": true
1442
+ },
1443
+ "128180": {
1444
+ "content": "<|reserved_special_token_172|>",
1445
+ "lstrip": false,
1446
+ "normalized": false,
1447
+ "rstrip": false,
1448
+ "single_word": false,
1449
+ "special": true
1450
+ },
1451
+ "128181": {
1452
+ "content": "<|reserved_special_token_173|>",
1453
+ "lstrip": false,
1454
+ "normalized": false,
1455
+ "rstrip": false,
1456
+ "single_word": false,
1457
+ "special": true
1458
+ },
1459
+ "128182": {
1460
+ "content": "<|reserved_special_token_174|>",
1461
+ "lstrip": false,
1462
+ "normalized": false,
1463
+ "rstrip": false,
1464
+ "single_word": false,
1465
+ "special": true
1466
+ },
1467
+ "128183": {
1468
+ "content": "<|reserved_special_token_175|>",
1469
+ "lstrip": false,
1470
+ "normalized": false,
1471
+ "rstrip": false,
1472
+ "single_word": false,
1473
+ "special": true
1474
+ },
1475
+ "128184": {
1476
+ "content": "<|reserved_special_token_176|>",
1477
+ "lstrip": false,
1478
+ "normalized": false,
1479
+ "rstrip": false,
1480
+ "single_word": false,
1481
+ "special": true
1482
+ },
1483
+ "128185": {
1484
+ "content": "<|reserved_special_token_177|>",
1485
+ "lstrip": false,
1486
+ "normalized": false,
1487
+ "rstrip": false,
1488
+ "single_word": false,
1489
+ "special": true
1490
+ },
1491
+ "128186": {
1492
+ "content": "<|reserved_special_token_178|>",
1493
+ "lstrip": false,
1494
+ "normalized": false,
1495
+ "rstrip": false,
1496
+ "single_word": false,
1497
+ "special": true
1498
+ },
1499
+ "128187": {
1500
+ "content": "<|reserved_special_token_179|>",
1501
+ "lstrip": false,
1502
+ "normalized": false,
1503
+ "rstrip": false,
1504
+ "single_word": false,
1505
+ "special": true
1506
+ },
1507
+ "128188": {
1508
+ "content": "<|reserved_special_token_180|>",
1509
+ "lstrip": false,
1510
+ "normalized": false,
1511
+ "rstrip": false,
1512
+ "single_word": false,
1513
+ "special": true
1514
+ },
1515
+ "128189": {
1516
+ "content": "<|reserved_special_token_181|>",
1517
+ "lstrip": false,
1518
+ "normalized": false,
1519
+ "rstrip": false,
1520
+ "single_word": false,
1521
+ "special": true
1522
+ },
1523
+ "128190": {
1524
+ "content": "<|reserved_special_token_182|>",
1525
+ "lstrip": false,
1526
+ "normalized": false,
1527
+ "rstrip": false,
1528
+ "single_word": false,
1529
+ "special": true
1530
+ },
1531
+ "128191": {
1532
+ "content": "<|reserved_special_token_183|>",
1533
+ "lstrip": false,
1534
+ "normalized": false,
1535
+ "rstrip": false,
1536
+ "single_word": false,
1537
+ "special": true
1538
+ },
1539
+ "128192": {
1540
+ "content": "<|reserved_special_token_184|>",
1541
+ "lstrip": false,
1542
+ "normalized": false,
1543
+ "rstrip": false,
1544
+ "single_word": false,
1545
+ "special": true
1546
+ },
1547
+ "128193": {
1548
+ "content": "<|reserved_special_token_185|>",
1549
+ "lstrip": false,
1550
+ "normalized": false,
1551
+ "rstrip": false,
1552
+ "single_word": false,
1553
+ "special": true
1554
+ },
1555
+ "128194": {
1556
+ "content": "<|reserved_special_token_186|>",
1557
+ "lstrip": false,
1558
+ "normalized": false,
1559
+ "rstrip": false,
1560
+ "single_word": false,
1561
+ "special": true
1562
+ },
1563
+ "128195": {
1564
+ "content": "<|reserved_special_token_187|>",
1565
+ "lstrip": false,
1566
+ "normalized": false,
1567
+ "rstrip": false,
1568
+ "single_word": false,
1569
+ "special": true
1570
+ },
1571
+ "128196": {
1572
+ "content": "<|reserved_special_token_188|>",
1573
+ "lstrip": false,
1574
+ "normalized": false,
1575
+ "rstrip": false,
1576
+ "single_word": false,
1577
+ "special": true
1578
+ },
1579
+ "128197": {
1580
+ "content": "<|reserved_special_token_189|>",
1581
+ "lstrip": false,
1582
+ "normalized": false,
1583
+ "rstrip": false,
1584
+ "single_word": false,
1585
+ "special": true
1586
+ },
1587
+ "128198": {
1588
+ "content": "<|reserved_special_token_190|>",
1589
+ "lstrip": false,
1590
+ "normalized": false,
1591
+ "rstrip": false,
1592
+ "single_word": false,
1593
+ "special": true
1594
+ },
1595
+ "128199": {
1596
+ "content": "<|reserved_special_token_191|>",
1597
+ "lstrip": false,
1598
+ "normalized": false,
1599
+ "rstrip": false,
1600
+ "single_word": false,
1601
+ "special": true
1602
+ },
1603
+ "128200": {
1604
+ "content": "<|reserved_special_token_192|>",
1605
+ "lstrip": false,
1606
+ "normalized": false,
1607
+ "rstrip": false,
1608
+ "single_word": false,
1609
+ "special": true
1610
+ },
1611
+ "128201": {
1612
+ "content": "<|reserved_special_token_193|>",
1613
+ "lstrip": false,
1614
+ "normalized": false,
1615
+ "rstrip": false,
1616
+ "single_word": false,
1617
+ "special": true
1618
+ },
1619
+ "128202": {
1620
+ "content": "<|reserved_special_token_194|>",
1621
+ "lstrip": false,
1622
+ "normalized": false,
1623
+ "rstrip": false,
1624
+ "single_word": false,
1625
+ "special": true
1626
+ },
1627
+ "128203": {
1628
+ "content": "<|reserved_special_token_195|>",
1629
+ "lstrip": false,
1630
+ "normalized": false,
1631
+ "rstrip": false,
1632
+ "single_word": false,
1633
+ "special": true
1634
+ },
1635
+ "128204": {
1636
+ "content": "<|reserved_special_token_196|>",
1637
+ "lstrip": false,
1638
+ "normalized": false,
1639
+ "rstrip": false,
1640
+ "single_word": false,
1641
+ "special": true
1642
+ },
1643
+ "128205": {
1644
+ "content": "<|reserved_special_token_197|>",
1645
+ "lstrip": false,
1646
+ "normalized": false,
1647
+ "rstrip": false,
1648
+ "single_word": false,
1649
+ "special": true
1650
+ },
1651
+ "128206": {
1652
+ "content": "<|reserved_special_token_198|>",
1653
+ "lstrip": false,
1654
+ "normalized": false,
1655
+ "rstrip": false,
1656
+ "single_word": false,
1657
+ "special": true
1658
+ },
1659
+ "128207": {
1660
+ "content": "<|reserved_special_token_199|>",
1661
+ "lstrip": false,
1662
+ "normalized": false,
1663
+ "rstrip": false,
1664
+ "single_word": false,
1665
+ "special": true
1666
+ },
1667
+ "128208": {
1668
+ "content": "<|reserved_special_token_200|>",
1669
+ "lstrip": false,
1670
+ "normalized": false,
1671
+ "rstrip": false,
1672
+ "single_word": false,
1673
+ "special": true
1674
+ },
1675
+ "128209": {
1676
+ "content": "<|reserved_special_token_201|>",
1677
+ "lstrip": false,
1678
+ "normalized": false,
1679
+ "rstrip": false,
1680
+ "single_word": false,
1681
+ "special": true
1682
+ },
1683
+ "128210": {
1684
+ "content": "<|reserved_special_token_202|>",
1685
+ "lstrip": false,
1686
+ "normalized": false,
1687
+ "rstrip": false,
1688
+ "single_word": false,
1689
+ "special": true
1690
+ },
1691
+ "128211": {
1692
+ "content": "<|reserved_special_token_203|>",
1693
+ "lstrip": false,
1694
+ "normalized": false,
1695
+ "rstrip": false,
1696
+ "single_word": false,
1697
+ "special": true
1698
+ },
1699
+ "128212": {
1700
+ "content": "<|reserved_special_token_204|>",
1701
+ "lstrip": false,
1702
+ "normalized": false,
1703
+ "rstrip": false,
1704
+ "single_word": false,
1705
+ "special": true
1706
+ },
1707
+ "128213": {
1708
+ "content": "<|reserved_special_token_205|>",
1709
+ "lstrip": false,
1710
+ "normalized": false,
1711
+ "rstrip": false,
1712
+ "single_word": false,
1713
+ "special": true
1714
+ },
1715
+ "128214": {
1716
+ "content": "<|reserved_special_token_206|>",
1717
+ "lstrip": false,
1718
+ "normalized": false,
1719
+ "rstrip": false,
1720
+ "single_word": false,
1721
+ "special": true
1722
+ },
1723
+ "128215": {
1724
+ "content": "<|reserved_special_token_207|>",
1725
+ "lstrip": false,
1726
+ "normalized": false,
1727
+ "rstrip": false,
1728
+ "single_word": false,
1729
+ "special": true
1730
+ },
1731
+ "128216": {
1732
+ "content": "<|reserved_special_token_208|>",
1733
+ "lstrip": false,
1734
+ "normalized": false,
1735
+ "rstrip": false,
1736
+ "single_word": false,
1737
+ "special": true
1738
+ },
1739
+ "128217": {
1740
+ "content": "<|reserved_special_token_209|>",
1741
+ "lstrip": false,
1742
+ "normalized": false,
1743
+ "rstrip": false,
1744
+ "single_word": false,
1745
+ "special": true
1746
+ },
1747
+ "128218": {
1748
+ "content": "<|reserved_special_token_210|>",
1749
+ "lstrip": false,
1750
+ "normalized": false,
1751
+ "rstrip": false,
1752
+ "single_word": false,
1753
+ "special": true
1754
+ },
1755
+ "128219": {
1756
+ "content": "<|reserved_special_token_211|>",
1757
+ "lstrip": false,
1758
+ "normalized": false,
1759
+ "rstrip": false,
1760
+ "single_word": false,
1761
+ "special": true
1762
+ },
1763
+ "128220": {
1764
+ "content": "<|reserved_special_token_212|>",
1765
+ "lstrip": false,
1766
+ "normalized": false,
1767
+ "rstrip": false,
1768
+ "single_word": false,
1769
+ "special": true
1770
+ },
1771
+ "128221": {
1772
+ "content": "<|reserved_special_token_213|>",
1773
+ "lstrip": false,
1774
+ "normalized": false,
1775
+ "rstrip": false,
1776
+ "single_word": false,
1777
+ "special": true
1778
+ },
1779
+ "128222": {
1780
+ "content": "<|reserved_special_token_214|>",
1781
+ "lstrip": false,
1782
+ "normalized": false,
1783
+ "rstrip": false,
1784
+ "single_word": false,
1785
+ "special": true
1786
+ },
1787
+ "128223": {
1788
+ "content": "<|reserved_special_token_215|>",
1789
+ "lstrip": false,
1790
+ "normalized": false,
1791
+ "rstrip": false,
1792
+ "single_word": false,
1793
+ "special": true
1794
+ },
1795
+ "128224": {
1796
+ "content": "<|reserved_special_token_216|>",
1797
+ "lstrip": false,
1798
+ "normalized": false,
1799
+ "rstrip": false,
1800
+ "single_word": false,
1801
+ "special": true
1802
+ },
1803
+ "128225": {
1804
+ "content": "<|reserved_special_token_217|>",
1805
+ "lstrip": false,
1806
+ "normalized": false,
1807
+ "rstrip": false,
1808
+ "single_word": false,
1809
+ "special": true
1810
+ },
1811
+ "128226": {
1812
+ "content": "<|reserved_special_token_218|>",
1813
+ "lstrip": false,
1814
+ "normalized": false,
1815
+ "rstrip": false,
1816
+ "single_word": false,
1817
+ "special": true
1818
+ },
1819
+ "128227": {
1820
+ "content": "<|reserved_special_token_219|>",
1821
+ "lstrip": false,
1822
+ "normalized": false,
1823
+ "rstrip": false,
1824
+ "single_word": false,
1825
+ "special": true
1826
+ },
1827
+ "128228": {
1828
+ "content": "<|reserved_special_token_220|>",
1829
+ "lstrip": false,
1830
+ "normalized": false,
1831
+ "rstrip": false,
1832
+ "single_word": false,
1833
+ "special": true
1834
+ },
1835
+ "128229": {
1836
+ "content": "<|reserved_special_token_221|>",
1837
+ "lstrip": false,
1838
+ "normalized": false,
1839
+ "rstrip": false,
1840
+ "single_word": false,
1841
+ "special": true
1842
+ },
1843
+ "128230": {
1844
+ "content": "<|reserved_special_token_222|>",
1845
+ "lstrip": false,
1846
+ "normalized": false,
1847
+ "rstrip": false,
1848
+ "single_word": false,
1849
+ "special": true
1850
+ },
1851
+ "128231": {
1852
+ "content": "<|reserved_special_token_223|>",
1853
+ "lstrip": false,
1854
+ "normalized": false,
1855
+ "rstrip": false,
1856
+ "single_word": false,
1857
+ "special": true
1858
+ },
1859
+ "128232": {
1860
+ "content": "<|reserved_special_token_224|>",
1861
+ "lstrip": false,
1862
+ "normalized": false,
1863
+ "rstrip": false,
1864
+ "single_word": false,
1865
+ "special": true
1866
+ },
1867
+ "128233": {
1868
+ "content": "<|reserved_special_token_225|>",
1869
+ "lstrip": false,
1870
+ "normalized": false,
1871
+ "rstrip": false,
1872
+ "single_word": false,
1873
+ "special": true
1874
+ },
1875
+ "128234": {
1876
+ "content": "<|reserved_special_token_226|>",
1877
+ "lstrip": false,
1878
+ "normalized": false,
1879
+ "rstrip": false,
1880
+ "single_word": false,
1881
+ "special": true
1882
+ },
1883
+ "128235": {
1884
+ "content": "<|reserved_special_token_227|>",
1885
+ "lstrip": false,
1886
+ "normalized": false,
1887
+ "rstrip": false,
1888
+ "single_word": false,
1889
+ "special": true
1890
+ },
1891
+ "128236": {
1892
+ "content": "<|reserved_special_token_228|>",
1893
+ "lstrip": false,
1894
+ "normalized": false,
1895
+ "rstrip": false,
1896
+ "single_word": false,
1897
+ "special": true
1898
+ },
1899
+ "128237": {
1900
+ "content": "<|reserved_special_token_229|>",
1901
+ "lstrip": false,
1902
+ "normalized": false,
1903
+ "rstrip": false,
1904
+ "single_word": false,
1905
+ "special": true
1906
+ },
1907
+ "128238": {
1908
+ "content": "<|reserved_special_token_230|>",
1909
+ "lstrip": false,
1910
+ "normalized": false,
1911
+ "rstrip": false,
1912
+ "single_word": false,
1913
+ "special": true
1914
+ },
1915
+ "128239": {
1916
+ "content": "<|reserved_special_token_231|>",
1917
+ "lstrip": false,
1918
+ "normalized": false,
1919
+ "rstrip": false,
1920
+ "single_word": false,
1921
+ "special": true
1922
+ },
1923
+ "128240": {
1924
+ "content": "<|reserved_special_token_232|>",
1925
+ "lstrip": false,
1926
+ "normalized": false,
1927
+ "rstrip": false,
1928
+ "single_word": false,
1929
+ "special": true
1930
+ },
1931
+ "128241": {
1932
+ "content": "<|reserved_special_token_233|>",
1933
+ "lstrip": false,
1934
+ "normalized": false,
1935
+ "rstrip": false,
1936
+ "single_word": false,
1937
+ "special": true
1938
+ },
1939
+ "128242": {
1940
+ "content": "<|reserved_special_token_234|>",
1941
+ "lstrip": false,
1942
+ "normalized": false,
1943
+ "rstrip": false,
1944
+ "single_word": false,
1945
+ "special": true
1946
+ },
1947
+ "128243": {
1948
+ "content": "<|reserved_special_token_235|>",
1949
+ "lstrip": false,
1950
+ "normalized": false,
1951
+ "rstrip": false,
1952
+ "single_word": false,
1953
+ "special": true
1954
+ },
1955
+ "128244": {
1956
+ "content": "<|reserved_special_token_236|>",
1957
+ "lstrip": false,
1958
+ "normalized": false,
1959
+ "rstrip": false,
1960
+ "single_word": false,
1961
+ "special": true
1962
+ },
1963
+ "128245": {
1964
+ "content": "<|reserved_special_token_237|>",
1965
+ "lstrip": false,
1966
+ "normalized": false,
1967
+ "rstrip": false,
1968
+ "single_word": false,
1969
+ "special": true
1970
+ },
1971
+ "128246": {
1972
+ "content": "<|reserved_special_token_238|>",
1973
+ "lstrip": false,
1974
+ "normalized": false,
1975
+ "rstrip": false,
1976
+ "single_word": false,
1977
+ "special": true
1978
+ },
1979
+ "128247": {
1980
+ "content": "<|reserved_special_token_239|>",
1981
+ "lstrip": false,
1982
+ "normalized": false,
1983
+ "rstrip": false,
1984
+ "single_word": false,
1985
+ "special": true
1986
+ },
1987
+ "128248": {
1988
+ "content": "<|reserved_special_token_240|>",
1989
+ "lstrip": false,
1990
+ "normalized": false,
1991
+ "rstrip": false,
1992
+ "single_word": false,
1993
+ "special": true
1994
+ },
1995
+ "128249": {
1996
+ "content": "<|reserved_special_token_241|>",
1997
+ "lstrip": false,
1998
+ "normalized": false,
1999
+ "rstrip": false,
2000
+ "single_word": false,
2001
+ "special": true
2002
+ },
2003
+ "128250": {
2004
+ "content": "<|reserved_special_token_242|>",
2005
+ "lstrip": false,
2006
+ "normalized": false,
2007
+ "rstrip": false,
2008
+ "single_word": false,
2009
+ "special": true
2010
+ },
2011
+ "128251": {
2012
+ "content": "<|reserved_special_token_243|>",
2013
+ "lstrip": false,
2014
+ "normalized": false,
2015
+ "rstrip": false,
2016
+ "single_word": false,
2017
+ "special": true
2018
+ },
2019
+ "128252": {
2020
+ "content": "<|reserved_special_token_244|>",
2021
+ "lstrip": false,
2022
+ "normalized": false,
2023
+ "rstrip": false,
2024
+ "single_word": false,
2025
+ "special": true
2026
+ },
2027
+ "128253": {
2028
+ "content": "<|reserved_special_token_245|>",
2029
+ "lstrip": false,
2030
+ "normalized": false,
2031
+ "rstrip": false,
2032
+ "single_word": false,
2033
+ "special": true
2034
+ },
2035
+ "128254": {
2036
+ "content": "<|reserved_special_token_246|>",
2037
+ "lstrip": false,
2038
+ "normalized": false,
2039
+ "rstrip": false,
2040
+ "single_word": false,
2041
+ "special": true
2042
+ },
2043
+ "128255": {
2044
+ "content": "<|reserved_special_token_247|>",
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": "{{- bos_token }}\n{%- if custom_tools is defined %}\n {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n {%- set tools_in_user_message = true %}\n{%- endif %}\n{%- if not date_string is defined %}\n {%- set date_string = \"26 Jul 2024\" %}\n{%- endif %}\n{%- if not tools is defined %}\n {%- set tools = none %}\n{%- endif %}\n\n{#- This block extracts the system message, so we can slot it into the right place. #}\n{%- if messages[0]['role'] == 'system' %}\n {%- set system_message = messages[0]['content']|trim %}\n {%- set messages = messages[1:] %}\n{%- else %}\n {%- set system_message = \"\" %}\n{%- endif %}\n\n{#- System message + builtin tools #}\n{{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n{%- if builtin_tools is defined or tools is not none %}\n {{- \"Environment: ipython\\n\" }}\n{%- endif %}\n{%- if builtin_tools is defined %}\n {{- \"Tools: \" + builtin_tools | reject('equalto', 'code_interpreter') | join(\", \") + \"\\n\\n\"}}\n{%- endif %}\n{{- \"Cutting Knowledge Date: December 2023\\n\" }}\n{{- \"Today Date: \" + date_string + \"\\n\\n\" }}\n{%- if tools is not none and not tools_in_user_message %}\n {{- \"You have access to the following functions. To call a function, please respond with JSON for a function call.\" }}\n {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n {{- \"Do not use variables.\\n\\n\" }}\n {%- for t in tools %}\n {{- t | tojson(indent=4) }}\n {{- \"\\n\\n\" }}\n {%- endfor %}\n{%- endif %}\n{{- system_message }}\n{{- \"<|eot_id|>\" }}\n\n{#- Custom tools are passed in a user message with some extra guidance #}\n{%- if tools_in_user_message and not tools is none %}\n {#- Extract the first user message so we can plug it in here #}\n {%- if messages | length != 0 %}\n {%- set first_user_message = messages[0]['content']|trim %}\n {%- set messages = messages[1:] %}\n {%- else %}\n {{- raise_exception(\"Cannot put tools in the first user message when there's no first user message!\") }}\n{%- endif %}\n {{- '<|start_header_id|>user<|end_header_id|>\\n\\n' -}}\n {{- \"Given the following functions, please respond with a JSON for a function call \" }}\n {{- \"with its proper arguments that best answers the given prompt.\\n\\n\" }}\n {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n {{- \"Do not use variables.\\n\\n\" }}\n {%- for t in tools %}\n {{- t | tojson(indent=4) }}\n {{- \"\\n\\n\" }}\n {%- endfor %}\n {{- first_user_message + \"<|eot_id|>\"}}\n{%- endif %}\n\n{%- for message in messages %}\n {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}\n {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n'+ message['content'] | trim + '<|eot_id|>' }}\n {%- elif 'tool_calls' in message %}\n {%- if not message.tool_calls|length == 1 %}\n {{- raise_exception(\"This model only supports single tool-calls at once!\") }}\n {%- endif %}\n {%- set tool_call = message.tool_calls[0].function %}\n {%- if builtin_tools is defined and tool_call.name in builtin_tools %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n {{- \"<|python_tag|>\" + tool_call.name + \".call(\" }}\n {%- for arg_name, arg_val in tool_call.arguments | items %}\n {{- arg_name + '=\"' + arg_val + '\"' }}\n {%- if not loop.last %}\n {{- \", \" }}\n {%- endif %}\n {%- endfor %}\n {{- \")\" }}\n {%- else %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n {{- '\"parameters\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- \"}\" }}\n {%- endif %}\n {%- if builtin_tools is defined %}\n {#- This means we're in ipython mode #}\n {{- \"<|eom_id|>\" }}\n {%- else %}\n {{- \"<|eot_id|>\" }}\n {%- endif %}\n {%- elif message.role == \"tool\" or message.role == \"ipython\" %}\n {{- \"<|start_header_id|>ipython<|end_header_id|>\\n\\n\" }}\n {%- if message.content is mapping or message.content is iterable %}\n {{- message.content | tojson }}\n {%- else %}\n {{- message.content }}\n {%- endif %}\n {{- \"<|eot_id|>\" }}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}\n{%- endif %}\n",
2054
+ "clean_up_tokenization_spaces": true,
2055
+ "eos_token": "<|eot_id|>",
2056
+ "extra_special_tokens": {},
2057
+ "model_input_names": [
2058
+ "input_ids",
2059
+ "attention_mask"
2060
+ ],
2061
+ "model_max_length": 131072,
2062
+ "pad_token": "<|end_of_text|>",
2063
+ "tokenizer_class": "PreTrainedTokenizer"
2064
+ }
checkpoint-432/trainer_state.json ADDED
@@ -0,0 +1,3057 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": null,
3
+ "best_model_checkpoint": null,
4
+ "epoch": 6.0,
5
+ "eval_steps": 500,
6
+ "global_step": 432,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.013888888888888888,
13
+ "grad_norm": 95.33702850341797,
14
+ "learning_rate": 5.0000000000000004e-08,
15
+ "loss": 5.3695,
16
+ "step": 1
17
+ },
18
+ {
19
+ "epoch": 0.027777777777777776,
20
+ "grad_norm": 96.05199432373047,
21
+ "learning_rate": 1.0000000000000001e-07,
22
+ "loss": 5.4178,
23
+ "step": 2
24
+ },
25
+ {
26
+ "epoch": 0.041666666666666664,
27
+ "grad_norm": 92.71851348876953,
28
+ "learning_rate": 1.5000000000000002e-07,
29
+ "loss": 5.4472,
30
+ "step": 3
31
+ },
32
+ {
33
+ "epoch": 0.05555555555555555,
34
+ "grad_norm": 95.78789520263672,
35
+ "learning_rate": 2.0000000000000002e-07,
36
+ "loss": 5.4114,
37
+ "step": 4
38
+ },
39
+ {
40
+ "epoch": 0.06944444444444445,
41
+ "grad_norm": 95.62769317626953,
42
+ "learning_rate": 2.5000000000000004e-07,
43
+ "loss": 5.3612,
44
+ "step": 5
45
+ },
46
+ {
47
+ "epoch": 0.08333333333333333,
48
+ "grad_norm": 94.85267639160156,
49
+ "learning_rate": 3.0000000000000004e-07,
50
+ "loss": 5.4065,
51
+ "step": 6
52
+ },
53
+ {
54
+ "epoch": 0.09722222222222222,
55
+ "grad_norm": 93.81153869628906,
56
+ "learning_rate": 3.5000000000000004e-07,
57
+ "loss": 5.364,
58
+ "step": 7
59
+ },
60
+ {
61
+ "epoch": 0.1111111111111111,
62
+ "grad_norm": 95.33504486083984,
63
+ "learning_rate": 4.0000000000000003e-07,
64
+ "loss": 5.4484,
65
+ "step": 8
66
+ },
67
+ {
68
+ "epoch": 0.125,
69
+ "grad_norm": 94.11618041992188,
70
+ "learning_rate": 4.5000000000000003e-07,
71
+ "loss": 5.3494,
72
+ "step": 9
73
+ },
74
+ {
75
+ "epoch": 0.1388888888888889,
76
+ "grad_norm": 93.71621704101562,
77
+ "learning_rate": 5.000000000000001e-07,
78
+ "loss": 5.2325,
79
+ "step": 10
80
+ },
81
+ {
82
+ "epoch": 0.1527777777777778,
83
+ "grad_norm": 92.6498031616211,
84
+ "learning_rate": 5.5e-07,
85
+ "loss": 5.1224,
86
+ "step": 11
87
+ },
88
+ {
89
+ "epoch": 0.16666666666666666,
90
+ "grad_norm": 89.05821228027344,
91
+ "learning_rate": 6.000000000000001e-07,
92
+ "loss": 5.0484,
93
+ "step": 12
94
+ },
95
+ {
96
+ "epoch": 0.18055555555555555,
97
+ "grad_norm": 87.52056884765625,
98
+ "learning_rate": 6.5e-07,
99
+ "loss": 4.8831,
100
+ "step": 13
101
+ },
102
+ {
103
+ "epoch": 0.19444444444444445,
104
+ "grad_norm": 87.93170928955078,
105
+ "learning_rate": 7.000000000000001e-07,
106
+ "loss": 4.7723,
107
+ "step": 14
108
+ },
109
+ {
110
+ "epoch": 0.20833333333333334,
111
+ "grad_norm": 84.07933044433594,
112
+ "learning_rate": 7.5e-07,
113
+ "loss": 4.5843,
114
+ "step": 15
115
+ },
116
+ {
117
+ "epoch": 0.2222222222222222,
118
+ "grad_norm": 82.16165161132812,
119
+ "learning_rate": 8.000000000000001e-07,
120
+ "loss": 4.4273,
121
+ "step": 16
122
+ },
123
+ {
124
+ "epoch": 0.2361111111111111,
125
+ "grad_norm": 78.94780731201172,
126
+ "learning_rate": 8.500000000000001e-07,
127
+ "loss": 4.155,
128
+ "step": 17
129
+ },
130
+ {
131
+ "epoch": 0.25,
132
+ "grad_norm": 75.85335540771484,
133
+ "learning_rate": 9.000000000000001e-07,
134
+ "loss": 3.9005,
135
+ "step": 18
136
+ },
137
+ {
138
+ "epoch": 0.2638888888888889,
139
+ "grad_norm": 71.74459075927734,
140
+ "learning_rate": 9.500000000000001e-07,
141
+ "loss": 3.5885,
142
+ "step": 19
143
+ },
144
+ {
145
+ "epoch": 0.2777777777777778,
146
+ "grad_norm": 67.66385650634766,
147
+ "learning_rate": 1.0000000000000002e-06,
148
+ "loss": 3.308,
149
+ "step": 20
150
+ },
151
+ {
152
+ "epoch": 0.2916666666666667,
153
+ "grad_norm": 64.22036743164062,
154
+ "learning_rate": 1.0500000000000001e-06,
155
+ "loss": 3.057,
156
+ "step": 21
157
+ },
158
+ {
159
+ "epoch": 0.3055555555555556,
160
+ "grad_norm": 60.24971008300781,
161
+ "learning_rate": 1.1e-06,
162
+ "loss": 2.7939,
163
+ "step": 22
164
+ },
165
+ {
166
+ "epoch": 0.3194444444444444,
167
+ "grad_norm": 57.68950271606445,
168
+ "learning_rate": 1.1500000000000002e-06,
169
+ "loss": 2.5539,
170
+ "step": 23
171
+ },
172
+ {
173
+ "epoch": 0.3333333333333333,
174
+ "grad_norm": 56.10525894165039,
175
+ "learning_rate": 1.2000000000000002e-06,
176
+ "loss": 2.2688,
177
+ "step": 24
178
+ },
179
+ {
180
+ "epoch": 0.3472222222222222,
181
+ "grad_norm": 54.84128189086914,
182
+ "learning_rate": 1.25e-06,
183
+ "loss": 2.009,
184
+ "step": 25
185
+ },
186
+ {
187
+ "epoch": 0.3611111111111111,
188
+ "grad_norm": 53.96566390991211,
189
+ "learning_rate": 1.3e-06,
190
+ "loss": 1.6682,
191
+ "step": 26
192
+ },
193
+ {
194
+ "epoch": 0.375,
195
+ "grad_norm": 53.859439849853516,
196
+ "learning_rate": 1.3500000000000002e-06,
197
+ "loss": 1.3807,
198
+ "step": 27
199
+ },
200
+ {
201
+ "epoch": 0.3888888888888889,
202
+ "grad_norm": 53.22216796875,
203
+ "learning_rate": 1.4000000000000001e-06,
204
+ "loss": 1.1229,
205
+ "step": 28
206
+ },
207
+ {
208
+ "epoch": 0.4027777777777778,
209
+ "grad_norm": 50.3905143737793,
210
+ "learning_rate": 1.45e-06,
211
+ "loss": 0.8454,
212
+ "step": 29
213
+ },
214
+ {
215
+ "epoch": 0.4166666666666667,
216
+ "grad_norm": 40.14346694946289,
217
+ "learning_rate": 1.5e-06,
218
+ "loss": 0.5817,
219
+ "step": 30
220
+ },
221
+ {
222
+ "epoch": 0.4305555555555556,
223
+ "grad_norm": 34.043235778808594,
224
+ "learning_rate": 1.5500000000000002e-06,
225
+ "loss": 0.4234,
226
+ "step": 31
227
+ },
228
+ {
229
+ "epoch": 0.4444444444444444,
230
+ "grad_norm": 28.703292846679688,
231
+ "learning_rate": 1.6000000000000001e-06,
232
+ "loss": 0.3074,
233
+ "step": 32
234
+ },
235
+ {
236
+ "epoch": 0.4583333333333333,
237
+ "grad_norm": 22.456626892089844,
238
+ "learning_rate": 1.6500000000000003e-06,
239
+ "loss": 0.2146,
240
+ "step": 33
241
+ },
242
+ {
243
+ "epoch": 0.4722222222222222,
244
+ "grad_norm": 15.350156784057617,
245
+ "learning_rate": 1.7000000000000002e-06,
246
+ "loss": 0.1103,
247
+ "step": 34
248
+ },
249
+ {
250
+ "epoch": 0.4861111111111111,
251
+ "grad_norm": 6.5175580978393555,
252
+ "learning_rate": 1.75e-06,
253
+ "loss": 0.0574,
254
+ "step": 35
255
+ },
256
+ {
257
+ "epoch": 0.5,
258
+ "grad_norm": 6.813859939575195,
259
+ "learning_rate": 1.8000000000000001e-06,
260
+ "loss": 0.0497,
261
+ "step": 36
262
+ },
263
+ {
264
+ "epoch": 0.5138888888888888,
265
+ "grad_norm": 3.5350818634033203,
266
+ "learning_rate": 1.85e-06,
267
+ "loss": 0.0199,
268
+ "step": 37
269
+ },
270
+ {
271
+ "epoch": 0.5277777777777778,
272
+ "grad_norm": 4.9657135009765625,
273
+ "learning_rate": 1.9000000000000002e-06,
274
+ "loss": 0.0245,
275
+ "step": 38
276
+ },
277
+ {
278
+ "epoch": 0.5416666666666666,
279
+ "grad_norm": 1.2266570329666138,
280
+ "learning_rate": 1.9500000000000004e-06,
281
+ "loss": 0.0087,
282
+ "step": 39
283
+ },
284
+ {
285
+ "epoch": 0.5555555555555556,
286
+ "grad_norm": 4.982794761657715,
287
+ "learning_rate": 2.0000000000000003e-06,
288
+ "loss": 0.048,
289
+ "step": 40
290
+ },
291
+ {
292
+ "epoch": 0.5694444444444444,
293
+ "grad_norm": 7.6967387199401855,
294
+ "learning_rate": 2.05e-06,
295
+ "loss": 0.0449,
296
+ "step": 41
297
+ },
298
+ {
299
+ "epoch": 0.5833333333333334,
300
+ "grad_norm": 2.9466323852539062,
301
+ "learning_rate": 2.1000000000000002e-06,
302
+ "loss": 0.0098,
303
+ "step": 42
304
+ },
305
+ {
306
+ "epoch": 0.5972222222222222,
307
+ "grad_norm": 2.191035747528076,
308
+ "learning_rate": 2.15e-06,
309
+ "loss": 0.0087,
310
+ "step": 43
311
+ },
312
+ {
313
+ "epoch": 0.6111111111111112,
314
+ "grad_norm": 7.3228840827941895,
315
+ "learning_rate": 2.2e-06,
316
+ "loss": 0.0339,
317
+ "step": 44
318
+ },
319
+ {
320
+ "epoch": 0.625,
321
+ "grad_norm": 4.737412929534912,
322
+ "learning_rate": 2.25e-06,
323
+ "loss": 0.0149,
324
+ "step": 45
325
+ },
326
+ {
327
+ "epoch": 0.6388888888888888,
328
+ "grad_norm": 1.7612887620925903,
329
+ "learning_rate": 2.3000000000000004e-06,
330
+ "loss": 0.0071,
331
+ "step": 46
332
+ },
333
+ {
334
+ "epoch": 0.6527777777777778,
335
+ "grad_norm": 3.344369649887085,
336
+ "learning_rate": 2.35e-06,
337
+ "loss": 0.0196,
338
+ "step": 47
339
+ },
340
+ {
341
+ "epoch": 0.6666666666666666,
342
+ "grad_norm": 2.2957704067230225,
343
+ "learning_rate": 2.4000000000000003e-06,
344
+ "loss": 0.0216,
345
+ "step": 48
346
+ },
347
+ {
348
+ "epoch": 0.6805555555555556,
349
+ "grad_norm": 1.83970308303833,
350
+ "learning_rate": 2.4500000000000003e-06,
351
+ "loss": 0.0221,
352
+ "step": 49
353
+ },
354
+ {
355
+ "epoch": 0.6944444444444444,
356
+ "grad_norm": 1.547287106513977,
357
+ "learning_rate": 2.5e-06,
358
+ "loss": 0.0061,
359
+ "step": 50
360
+ },
361
+ {
362
+ "epoch": 0.7083333333333334,
363
+ "grad_norm": 1.6580262184143066,
364
+ "learning_rate": 2.55e-06,
365
+ "loss": 0.0127,
366
+ "step": 51
367
+ },
368
+ {
369
+ "epoch": 0.7222222222222222,
370
+ "grad_norm": 1.8863849639892578,
371
+ "learning_rate": 2.6e-06,
372
+ "loss": 0.0124,
373
+ "step": 52
374
+ },
375
+ {
376
+ "epoch": 0.7361111111111112,
377
+ "grad_norm": 1.2086963653564453,
378
+ "learning_rate": 2.6500000000000005e-06,
379
+ "loss": 0.0085,
380
+ "step": 53
381
+ },
382
+ {
383
+ "epoch": 0.75,
384
+ "grad_norm": 2.4265427589416504,
385
+ "learning_rate": 2.7000000000000004e-06,
386
+ "loss": 0.0255,
387
+ "step": 54
388
+ },
389
+ {
390
+ "epoch": 0.7638888888888888,
391
+ "grad_norm": 2.0333855152130127,
392
+ "learning_rate": 2.7500000000000004e-06,
393
+ "loss": 0.0145,
394
+ "step": 55
395
+ },
396
+ {
397
+ "epoch": 0.7777777777777778,
398
+ "grad_norm": 2.9129791259765625,
399
+ "learning_rate": 2.8000000000000003e-06,
400
+ "loss": 0.0228,
401
+ "step": 56
402
+ },
403
+ {
404
+ "epoch": 0.7916666666666666,
405
+ "grad_norm": 0.8359552621841431,
406
+ "learning_rate": 2.85e-06,
407
+ "loss": 0.0109,
408
+ "step": 57
409
+ },
410
+ {
411
+ "epoch": 0.8055555555555556,
412
+ "grad_norm": 1.677287220954895,
413
+ "learning_rate": 2.9e-06,
414
+ "loss": 0.0246,
415
+ "step": 58
416
+ },
417
+ {
418
+ "epoch": 0.8194444444444444,
419
+ "grad_norm": 1.0761189460754395,
420
+ "learning_rate": 2.95e-06,
421
+ "loss": 0.0058,
422
+ "step": 59
423
+ },
424
+ {
425
+ "epoch": 0.8333333333333334,
426
+ "grad_norm": 1.1098495721817017,
427
+ "learning_rate": 3e-06,
428
+ "loss": 0.0167,
429
+ "step": 60
430
+ },
431
+ {
432
+ "epoch": 0.8472222222222222,
433
+ "grad_norm": 1.0377463102340698,
434
+ "learning_rate": 3.05e-06,
435
+ "loss": 0.007,
436
+ "step": 61
437
+ },
438
+ {
439
+ "epoch": 0.8611111111111112,
440
+ "grad_norm": 0.6554276347160339,
441
+ "learning_rate": 3.1000000000000004e-06,
442
+ "loss": 0.0039,
443
+ "step": 62
444
+ },
445
+ {
446
+ "epoch": 0.875,
447
+ "grad_norm": 1.279077410697937,
448
+ "learning_rate": 3.1500000000000003e-06,
449
+ "loss": 0.0199,
450
+ "step": 63
451
+ },
452
+ {
453
+ "epoch": 0.8888888888888888,
454
+ "grad_norm": 0.7709833979606628,
455
+ "learning_rate": 3.2000000000000003e-06,
456
+ "loss": 0.0043,
457
+ "step": 64
458
+ },
459
+ {
460
+ "epoch": 0.9027777777777778,
461
+ "grad_norm": 1.3619827032089233,
462
+ "learning_rate": 3.2500000000000002e-06,
463
+ "loss": 0.0067,
464
+ "step": 65
465
+ },
466
+ {
467
+ "epoch": 0.9166666666666666,
468
+ "grad_norm": 1.3849765062332153,
469
+ "learning_rate": 3.3000000000000006e-06,
470
+ "loss": 0.0091,
471
+ "step": 66
472
+ },
473
+ {
474
+ "epoch": 0.9305555555555556,
475
+ "grad_norm": 1.1380351781845093,
476
+ "learning_rate": 3.3500000000000005e-06,
477
+ "loss": 0.0143,
478
+ "step": 67
479
+ },
480
+ {
481
+ "epoch": 0.9444444444444444,
482
+ "grad_norm": 1.9759573936462402,
483
+ "learning_rate": 3.4000000000000005e-06,
484
+ "loss": 0.0231,
485
+ "step": 68
486
+ },
487
+ {
488
+ "epoch": 0.9583333333333334,
489
+ "grad_norm": 0.5920725464820862,
490
+ "learning_rate": 3.45e-06,
491
+ "loss": 0.0063,
492
+ "step": 69
493
+ },
494
+ {
495
+ "epoch": 0.9722222222222222,
496
+ "grad_norm": 1.2489631175994873,
497
+ "learning_rate": 3.5e-06,
498
+ "loss": 0.0149,
499
+ "step": 70
500
+ },
501
+ {
502
+ "epoch": 0.9861111111111112,
503
+ "grad_norm": 1.5553513765335083,
504
+ "learning_rate": 3.5500000000000003e-06,
505
+ "loss": 0.0085,
506
+ "step": 71
507
+ },
508
+ {
509
+ "epoch": 1.0,
510
+ "grad_norm": 1.0278698205947876,
511
+ "learning_rate": 3.6000000000000003e-06,
512
+ "loss": 0.0061,
513
+ "step": 72
514
+ },
515
+ {
516
+ "epoch": 1.0138888888888888,
517
+ "grad_norm": 1.9279776811599731,
518
+ "learning_rate": 3.65e-06,
519
+ "loss": 0.0118,
520
+ "step": 73
521
+ },
522
+ {
523
+ "epoch": 1.0277777777777777,
524
+ "grad_norm": 2.592510223388672,
525
+ "learning_rate": 3.7e-06,
526
+ "loss": 0.0309,
527
+ "step": 74
528
+ },
529
+ {
530
+ "epoch": 1.0416666666666667,
531
+ "grad_norm": 1.6530096530914307,
532
+ "learning_rate": 3.7500000000000005e-06,
533
+ "loss": 0.0099,
534
+ "step": 75
535
+ },
536
+ {
537
+ "epoch": 1.0555555555555556,
538
+ "grad_norm": 0.4624968469142914,
539
+ "learning_rate": 3.8000000000000005e-06,
540
+ "loss": 0.0053,
541
+ "step": 76
542
+ },
543
+ {
544
+ "epoch": 1.0694444444444444,
545
+ "grad_norm": 0.629607617855072,
546
+ "learning_rate": 3.85e-06,
547
+ "loss": 0.0087,
548
+ "step": 77
549
+ },
550
+ {
551
+ "epoch": 1.0833333333333333,
552
+ "grad_norm": 0.14678587019443512,
553
+ "learning_rate": 3.900000000000001e-06,
554
+ "loss": 0.0007,
555
+ "step": 78
556
+ },
557
+ {
558
+ "epoch": 1.0972222222222223,
559
+ "grad_norm": 1.0052955150604248,
560
+ "learning_rate": 3.95e-06,
561
+ "loss": 0.0089,
562
+ "step": 79
563
+ },
564
+ {
565
+ "epoch": 1.1111111111111112,
566
+ "grad_norm": 0.9059052467346191,
567
+ "learning_rate": 4.000000000000001e-06,
568
+ "loss": 0.0049,
569
+ "step": 80
570
+ },
571
+ {
572
+ "epoch": 1.125,
573
+ "grad_norm": 0.871515691280365,
574
+ "learning_rate": 4.05e-06,
575
+ "loss": 0.0092,
576
+ "step": 81
577
+ },
578
+ {
579
+ "epoch": 1.1388888888888888,
580
+ "grad_norm": 0.07520482689142227,
581
+ "learning_rate": 4.1e-06,
582
+ "loss": 0.0004,
583
+ "step": 82
584
+ },
585
+ {
586
+ "epoch": 1.1527777777777777,
587
+ "grad_norm": 0.8039830923080444,
588
+ "learning_rate": 4.15e-06,
589
+ "loss": 0.0031,
590
+ "step": 83
591
+ },
592
+ {
593
+ "epoch": 1.1666666666666667,
594
+ "grad_norm": 0.05209676921367645,
595
+ "learning_rate": 4.2000000000000004e-06,
596
+ "loss": 0.0003,
597
+ "step": 84
598
+ },
599
+ {
600
+ "epoch": 1.1805555555555556,
601
+ "grad_norm": 0.04410432651638985,
602
+ "learning_rate": 4.25e-06,
603
+ "loss": 0.0002,
604
+ "step": 85
605
+ },
606
+ {
607
+ "epoch": 1.1944444444444444,
608
+ "grad_norm": 0.06021099537611008,
609
+ "learning_rate": 4.3e-06,
610
+ "loss": 0.0002,
611
+ "step": 86
612
+ },
613
+ {
614
+ "epoch": 1.2083333333333333,
615
+ "grad_norm": 0.283663272857666,
616
+ "learning_rate": 4.350000000000001e-06,
617
+ "loss": 0.001,
618
+ "step": 87
619
+ },
620
+ {
621
+ "epoch": 1.2222222222222223,
622
+ "grad_norm": 0.6798669695854187,
623
+ "learning_rate": 4.4e-06,
624
+ "loss": 0.0033,
625
+ "step": 88
626
+ },
627
+ {
628
+ "epoch": 1.2361111111111112,
629
+ "grad_norm": 0.06857122480869293,
630
+ "learning_rate": 4.450000000000001e-06,
631
+ "loss": 0.0002,
632
+ "step": 89
633
+ },
634
+ {
635
+ "epoch": 1.25,
636
+ "grad_norm": 1.9897412061691284,
637
+ "learning_rate": 4.5e-06,
638
+ "loss": 0.0126,
639
+ "step": 90
640
+ },
641
+ {
642
+ "epoch": 1.2638888888888888,
643
+ "grad_norm": 1.2174546718597412,
644
+ "learning_rate": 4.5500000000000005e-06,
645
+ "loss": 0.0023,
646
+ "step": 91
647
+ },
648
+ {
649
+ "epoch": 1.2777777777777777,
650
+ "grad_norm": 2.2762115001678467,
651
+ "learning_rate": 4.600000000000001e-06,
652
+ "loss": 0.0095,
653
+ "step": 92
654
+ },
655
+ {
656
+ "epoch": 1.2916666666666667,
657
+ "grad_norm": 3.728581428527832,
658
+ "learning_rate": 4.65e-06,
659
+ "loss": 0.0046,
660
+ "step": 93
661
+ },
662
+ {
663
+ "epoch": 1.3055555555555556,
664
+ "grad_norm": 2.942180871963501,
665
+ "learning_rate": 4.7e-06,
666
+ "loss": 0.0261,
667
+ "step": 94
668
+ },
669
+ {
670
+ "epoch": 1.3194444444444444,
671
+ "grad_norm": 0.3911007344722748,
672
+ "learning_rate": 4.75e-06,
673
+ "loss": 0.0005,
674
+ "step": 95
675
+ },
676
+ {
677
+ "epoch": 1.3333333333333333,
678
+ "grad_norm": 0.03832005336880684,
679
+ "learning_rate": 4.800000000000001e-06,
680
+ "loss": 0.0001,
681
+ "step": 96
682
+ },
683
+ {
684
+ "epoch": 1.3472222222222223,
685
+ "grad_norm": 0.7516991496086121,
686
+ "learning_rate": 4.85e-06,
687
+ "loss": 0.0017,
688
+ "step": 97
689
+ },
690
+ {
691
+ "epoch": 1.3611111111111112,
692
+ "grad_norm": 0.4136435091495514,
693
+ "learning_rate": 4.9000000000000005e-06,
694
+ "loss": 0.0014,
695
+ "step": 98
696
+ },
697
+ {
698
+ "epoch": 1.375,
699
+ "grad_norm": 0.044784627854824066,
700
+ "learning_rate": 4.95e-06,
701
+ "loss": 0.0001,
702
+ "step": 99
703
+ },
704
+ {
705
+ "epoch": 1.3888888888888888,
706
+ "grad_norm": 0.7667476534843445,
707
+ "learning_rate": 5e-06,
708
+ "loss": 0.0022,
709
+ "step": 100
710
+ },
711
+ {
712
+ "epoch": 1.4027777777777777,
713
+ "grad_norm": 0.9187825322151184,
714
+ "learning_rate": 4.999888074163108e-06,
715
+ "loss": 0.0035,
716
+ "step": 101
717
+ },
718
+ {
719
+ "epoch": 1.4166666666666667,
720
+ "grad_norm": 1.2859818935394287,
721
+ "learning_rate": 4.999552306674345e-06,
722
+ "loss": 0.0046,
723
+ "step": 102
724
+ },
725
+ {
726
+ "epoch": 1.4305555555555556,
727
+ "grad_norm": 0.5899283289909363,
728
+ "learning_rate": 4.998992727598557e-06,
729
+ "loss": 0.0027,
730
+ "step": 103
731
+ },
732
+ {
733
+ "epoch": 1.4444444444444444,
734
+ "grad_norm": 0.027552006766200066,
735
+ "learning_rate": 4.998209387040829e-06,
736
+ "loss": 0.0001,
737
+ "step": 104
738
+ },
739
+ {
740
+ "epoch": 1.4583333333333333,
741
+ "grad_norm": 0.14271241426467896,
742
+ "learning_rate": 4.9972023551419995e-06,
743
+ "loss": 0.0002,
744
+ "step": 105
745
+ },
746
+ {
747
+ "epoch": 1.4722222222222223,
748
+ "grad_norm": 0.36476054787635803,
749
+ "learning_rate": 4.995971722072379e-06,
750
+ "loss": 0.001,
751
+ "step": 106
752
+ },
753
+ {
754
+ "epoch": 1.4861111111111112,
755
+ "grad_norm": 1.7742875814437866,
756
+ "learning_rate": 4.9945175980236745e-06,
757
+ "loss": 0.0025,
758
+ "step": 107
759
+ },
760
+ {
761
+ "epoch": 1.5,
762
+ "grad_norm": 0.5356531739234924,
763
+ "learning_rate": 4.992840113199131e-06,
764
+ "loss": 0.0011,
765
+ "step": 108
766
+ },
767
+ {
768
+ "epoch": 1.5138888888888888,
769
+ "grad_norm": 0.9400438070297241,
770
+ "learning_rate": 4.990939417801859e-06,
771
+ "loss": 0.0021,
772
+ "step": 109
773
+ },
774
+ {
775
+ "epoch": 1.5277777777777777,
776
+ "grad_norm": 0.028793074190616608,
777
+ "learning_rate": 4.988815682021398e-06,
778
+ "loss": 0.0001,
779
+ "step": 110
780
+ },
781
+ {
782
+ "epoch": 1.5416666666666665,
783
+ "grad_norm": 0.016167419031262398,
784
+ "learning_rate": 4.986469096018472e-06,
785
+ "loss": 0.0001,
786
+ "step": 111
787
+ },
788
+ {
789
+ "epoch": 1.5555555555555556,
790
+ "grad_norm": 0.04863646626472473,
791
+ "learning_rate": 4.983899869907963e-06,
792
+ "loss": 0.0001,
793
+ "step": 112
794
+ },
795
+ {
796
+ "epoch": 1.5694444444444444,
797
+ "grad_norm": 0.11991345882415771,
798
+ "learning_rate": 4.981108233740096e-06,
799
+ "loss": 0.0003,
800
+ "step": 113
801
+ },
802
+ {
803
+ "epoch": 1.5833333333333335,
804
+ "grad_norm": 1.1984789371490479,
805
+ "learning_rate": 4.978094437479843e-06,
806
+ "loss": 0.0205,
807
+ "step": 114
808
+ },
809
+ {
810
+ "epoch": 1.5972222222222223,
811
+ "grad_norm": 0.2907632887363434,
812
+ "learning_rate": 4.97485875098454e-06,
813
+ "loss": 0.0005,
814
+ "step": 115
815
+ },
816
+ {
817
+ "epoch": 1.6111111111111112,
818
+ "grad_norm": 2.186234474182129,
819
+ "learning_rate": 4.971401463979722e-06,
820
+ "loss": 0.0068,
821
+ "step": 116
822
+ },
823
+ {
824
+ "epoch": 1.625,
825
+ "grad_norm": 0.17205508053302765,
826
+ "learning_rate": 4.967722886033181e-06,
827
+ "loss": 0.0004,
828
+ "step": 117
829
+ },
830
+ {
831
+ "epoch": 1.6388888888888888,
832
+ "grad_norm": 1.9445418119430542,
833
+ "learning_rate": 4.963823346527249e-06,
834
+ "loss": 0.0052,
835
+ "step": 118
836
+ },
837
+ {
838
+ "epoch": 1.6527777777777777,
839
+ "grad_norm": 0.8023346662521362,
840
+ "learning_rate": 4.959703194629304e-06,
841
+ "loss": 0.0087,
842
+ "step": 119
843
+ },
844
+ {
845
+ "epoch": 1.6666666666666665,
846
+ "grad_norm": 0.4967271685600281,
847
+ "learning_rate": 4.955362799260507e-06,
848
+ "loss": 0.0011,
849
+ "step": 120
850
+ },
851
+ {
852
+ "epoch": 1.6805555555555556,
853
+ "grad_norm": 0.18211083114147186,
854
+ "learning_rate": 4.950802549062764e-06,
855
+ "loss": 0.0007,
856
+ "step": 121
857
+ },
858
+ {
859
+ "epoch": 1.6944444444444444,
860
+ "grad_norm": 0.2594281733036041,
861
+ "learning_rate": 4.946022852363932e-06,
862
+ "loss": 0.0011,
863
+ "step": 122
864
+ },
865
+ {
866
+ "epoch": 1.7083333333333335,
867
+ "grad_norm": 0.8132149577140808,
868
+ "learning_rate": 4.9410241371412525e-06,
869
+ "loss": 0.0023,
870
+ "step": 123
871
+ },
872
+ {
873
+ "epoch": 1.7222222222222223,
874
+ "grad_norm": 0.27094146609306335,
875
+ "learning_rate": 4.935806850983034e-06,
876
+ "loss": 0.001,
877
+ "step": 124
878
+ },
879
+ {
880
+ "epoch": 1.7361111111111112,
881
+ "grad_norm": 0.10404836386442184,
882
+ "learning_rate": 4.9303714610485705e-06,
883
+ "loss": 0.0005,
884
+ "step": 125
885
+ },
886
+ {
887
+ "epoch": 1.75,
888
+ "grad_norm": 0.9027087688446045,
889
+ "learning_rate": 4.924718454026318e-06,
890
+ "loss": 0.005,
891
+ "step": 126
892
+ },
893
+ {
894
+ "epoch": 1.7638888888888888,
895
+ "grad_norm": 0.3427490293979645,
896
+ "learning_rate": 4.918848336090309e-06,
897
+ "loss": 0.0013,
898
+ "step": 127
899
+ },
900
+ {
901
+ "epoch": 1.7777777777777777,
902
+ "grad_norm": 0.41760626435279846,
903
+ "learning_rate": 4.912761632854834e-06,
904
+ "loss": 0.0032,
905
+ "step": 128
906
+ },
907
+ {
908
+ "epoch": 1.7916666666666665,
909
+ "grad_norm": 0.09792769700288773,
910
+ "learning_rate": 4.906458889327375e-06,
911
+ "loss": 0.0004,
912
+ "step": 129
913
+ },
914
+ {
915
+ "epoch": 1.8055555555555556,
916
+ "grad_norm": 0.5523985624313354,
917
+ "learning_rate": 4.899940669859807e-06,
918
+ "loss": 0.0077,
919
+ "step": 130
920
+ },
921
+ {
922
+ "epoch": 1.8194444444444444,
923
+ "grad_norm": 0.15261663496494293,
924
+ "learning_rate": 4.893207558097867e-06,
925
+ "loss": 0.0007,
926
+ "step": 131
927
+ },
928
+ {
929
+ "epoch": 1.8333333333333335,
930
+ "grad_norm": 0.12152901291847229,
931
+ "learning_rate": 4.8862601569288885e-06,
932
+ "loss": 0.0005,
933
+ "step": 132
934
+ },
935
+ {
936
+ "epoch": 1.8472222222222223,
937
+ "grad_norm": 0.1660558432340622,
938
+ "learning_rate": 4.879099088427824e-06,
939
+ "loss": 0.0007,
940
+ "step": 133
941
+ },
942
+ {
943
+ "epoch": 1.8611111111111112,
944
+ "grad_norm": 0.45732977986335754,
945
+ "learning_rate": 4.871724993801541e-06,
946
+ "loss": 0.0008,
947
+ "step": 134
948
+ },
949
+ {
950
+ "epoch": 1.875,
951
+ "grad_norm": 0.1277359277009964,
952
+ "learning_rate": 4.864138533331411e-06,
953
+ "loss": 0.0004,
954
+ "step": 135
955
+ },
956
+ {
957
+ "epoch": 1.8888888888888888,
958
+ "grad_norm": 0.08218172937631607,
959
+ "learning_rate": 4.8563403863141825e-06,
960
+ "loss": 0.0003,
961
+ "step": 136
962
+ },
963
+ {
964
+ "epoch": 1.9027777777777777,
965
+ "grad_norm": 0.35776910185813904,
966
+ "learning_rate": 4.84833125100116e-06,
967
+ "loss": 0.0012,
968
+ "step": 137
969
+ },
970
+ {
971
+ "epoch": 1.9166666666666665,
972
+ "grad_norm": 0.11485318094491959,
973
+ "learning_rate": 4.840111844535682e-06,
974
+ "loss": 0.0004,
975
+ "step": 138
976
+ },
977
+ {
978
+ "epoch": 1.9305555555555556,
979
+ "grad_norm": 0.03145573288202286,
980
+ "learning_rate": 4.8316829028889076e-06,
981
+ "loss": 0.0001,
982
+ "step": 139
983
+ },
984
+ {
985
+ "epoch": 1.9444444444444444,
986
+ "grad_norm": 0.03419964388012886,
987
+ "learning_rate": 4.823045180793914e-06,
988
+ "loss": 0.0001,
989
+ "step": 140
990
+ },
991
+ {
992
+ "epoch": 1.9583333333333335,
993
+ "grad_norm": 0.008005158044397831,
994
+ "learning_rate": 4.8141994516781196e-06,
995
+ "loss": 0.0,
996
+ "step": 141
997
+ },
998
+ {
999
+ "epoch": 1.9722222222222223,
1000
+ "grad_norm": 0.30687257647514343,
1001
+ "learning_rate": 4.805146507594034e-06,
1002
+ "loss": 0.0006,
1003
+ "step": 142
1004
+ },
1005
+ {
1006
+ "epoch": 1.9861111111111112,
1007
+ "grad_norm": 0.0030141561292111874,
1008
+ "learning_rate": 4.7958871591483305e-06,
1009
+ "loss": 0.0,
1010
+ "step": 143
1011
+ },
1012
+ {
1013
+ "epoch": 2.0,
1014
+ "grad_norm": 0.0026682906318455935,
1015
+ "learning_rate": 4.786422235429269e-06,
1016
+ "loss": 0.0,
1017
+ "step": 144
1018
+ },
1019
+ {
1020
+ "epoch": 2.013888888888889,
1021
+ "grad_norm": 0.008881614543497562,
1022
+ "learning_rate": 4.776752583932455e-06,
1023
+ "loss": 0.0,
1024
+ "step": 145
1025
+ },
1026
+ {
1027
+ "epoch": 2.0277777777777777,
1028
+ "grad_norm": 0.001991939265280962,
1029
+ "learning_rate": 4.766879070484957e-06,
1030
+ "loss": 0.0,
1031
+ "step": 146
1032
+ },
1033
+ {
1034
+ "epoch": 2.0416666666666665,
1035
+ "grad_norm": 0.006773048546165228,
1036
+ "learning_rate": 4.756802579167781e-06,
1037
+ "loss": 0.0,
1038
+ "step": 147
1039
+ },
1040
+ {
1041
+ "epoch": 2.0555555555555554,
1042
+ "grad_norm": 0.00205055414699018,
1043
+ "learning_rate": 4.746524012236706e-06,
1044
+ "loss": 0.0,
1045
+ "step": 148
1046
+ },
1047
+ {
1048
+ "epoch": 2.0694444444444446,
1049
+ "grad_norm": 0.0041306703351438046,
1050
+ "learning_rate": 4.736044290041496e-06,
1051
+ "loss": 0.0,
1052
+ "step": 149
1053
+ },
1054
+ {
1055
+ "epoch": 2.0833333333333335,
1056
+ "grad_norm": 0.001996932551264763,
1057
+ "learning_rate": 4.725364350943492e-06,
1058
+ "loss": 0.0,
1059
+ "step": 150
1060
+ },
1061
+ {
1062
+ "epoch": 2.0972222222222223,
1063
+ "grad_norm": 0.003478364087641239,
1064
+ "learning_rate": 4.714485151231593e-06,
1065
+ "loss": 0.0,
1066
+ "step": 151
1067
+ },
1068
+ {
1069
+ "epoch": 2.111111111111111,
1070
+ "grad_norm": 0.01027267798781395,
1071
+ "learning_rate": 4.703407665036622e-06,
1072
+ "loss": 0.0,
1073
+ "step": 152
1074
+ },
1075
+ {
1076
+ "epoch": 2.125,
1077
+ "grad_norm": 0.0020006722770631313,
1078
+ "learning_rate": 4.692132884244113e-06,
1079
+ "loss": 0.0,
1080
+ "step": 153
1081
+ },
1082
+ {
1083
+ "epoch": 2.138888888888889,
1084
+ "grad_norm": 0.006151544861495495,
1085
+ "learning_rate": 4.680661818405485e-06,
1086
+ "loss": 0.0,
1087
+ "step": 154
1088
+ },
1089
+ {
1090
+ "epoch": 2.1527777777777777,
1091
+ "grad_norm": 0.0020251101814210415,
1092
+ "learning_rate": 4.668995494647653e-06,
1093
+ "loss": 0.0,
1094
+ "step": 155
1095
+ },
1096
+ {
1097
+ "epoch": 2.1666666666666665,
1098
+ "grad_norm": 0.0021893251687288284,
1099
+ "learning_rate": 4.657134957581057e-06,
1100
+ "loss": 0.0,
1101
+ "step": 156
1102
+ },
1103
+ {
1104
+ "epoch": 2.1805555555555554,
1105
+ "grad_norm": 0.0018878229893743992,
1106
+ "learning_rate": 4.645081269206128e-06,
1107
+ "loss": 0.0,
1108
+ "step": 157
1109
+ },
1110
+ {
1111
+ "epoch": 2.1944444444444446,
1112
+ "grad_norm": 0.759505569934845,
1113
+ "learning_rate": 4.632835508818192e-06,
1114
+ "loss": 0.0002,
1115
+ "step": 158
1116
+ },
1117
+ {
1118
+ "epoch": 2.2083333333333335,
1119
+ "grad_norm": 0.0018357271328568459,
1120
+ "learning_rate": 4.620398772910833e-06,
1121
+ "loss": 0.0,
1122
+ "step": 159
1123
+ },
1124
+ {
1125
+ "epoch": 2.2222222222222223,
1126
+ "grad_norm": 0.001739851082675159,
1127
+ "learning_rate": 4.607772175077712e-06,
1128
+ "loss": 0.0,
1129
+ "step": 160
1130
+ },
1131
+ {
1132
+ "epoch": 2.236111111111111,
1133
+ "grad_norm": 0.0031391726806759834,
1134
+ "learning_rate": 4.59495684591285e-06,
1135
+ "loss": 0.0,
1136
+ "step": 161
1137
+ },
1138
+ {
1139
+ "epoch": 2.25,
1140
+ "grad_norm": 0.001889107865281403,
1141
+ "learning_rate": 4.581953932909403e-06,
1142
+ "loss": 0.0,
1143
+ "step": 162
1144
+ },
1145
+ {
1146
+ "epoch": 2.263888888888889,
1147
+ "grad_norm": 0.0014751956332474947,
1148
+ "learning_rate": 4.5687646003569055e-06,
1149
+ "loss": 0.0,
1150
+ "step": 163
1151
+ },
1152
+ {
1153
+ "epoch": 2.2777777777777777,
1154
+ "grad_norm": 0.0014328192919492722,
1155
+ "learning_rate": 4.555390029237026e-06,
1156
+ "loss": 0.0,
1157
+ "step": 164
1158
+ },
1159
+ {
1160
+ "epoch": 2.2916666666666665,
1161
+ "grad_norm": 0.0014799810014665127,
1162
+ "learning_rate": 4.541831417117815e-06,
1163
+ "loss": 0.0,
1164
+ "step": 165
1165
+ },
1166
+ {
1167
+ "epoch": 2.3055555555555554,
1168
+ "grad_norm": 0.0013504689559340477,
1169
+ "learning_rate": 4.528089978046481e-06,
1170
+ "loss": 0.0,
1171
+ "step": 166
1172
+ },
1173
+ {
1174
+ "epoch": 2.3194444444444446,
1175
+ "grad_norm": 0.001344231073744595,
1176
+ "learning_rate": 4.514166942440679e-06,
1177
+ "loss": 0.0,
1178
+ "step": 167
1179
+ },
1180
+ {
1181
+ "epoch": 2.3333333333333335,
1182
+ "grad_norm": 0.001366922864690423,
1183
+ "learning_rate": 4.5000635569783365e-06,
1184
+ "loss": 0.0,
1185
+ "step": 168
1186
+ },
1187
+ {
1188
+ "epoch": 2.3472222222222223,
1189
+ "grad_norm": 0.0013009505346417427,
1190
+ "learning_rate": 4.4857810844860325e-06,
1191
+ "loss": 0.0,
1192
+ "step": 169
1193
+ },
1194
+ {
1195
+ "epoch": 2.361111111111111,
1196
+ "grad_norm": 0.001247942098416388,
1197
+ "learning_rate": 4.471320803825915e-06,
1198
+ "loss": 0.0,
1199
+ "step": 170
1200
+ },
1201
+ {
1202
+ "epoch": 2.375,
1203
+ "grad_norm": 0.0011512853670865297,
1204
+ "learning_rate": 4.4566840097811956e-06,
1205
+ "loss": 0.0,
1206
+ "step": 171
1207
+ },
1208
+ {
1209
+ "epoch": 2.388888888888889,
1210
+ "grad_norm": 0.001167183741927147,
1211
+ "learning_rate": 4.4418720129402145e-06,
1212
+ "loss": 0.0,
1213
+ "step": 172
1214
+ },
1215
+ {
1216
+ "epoch": 2.4027777777777777,
1217
+ "grad_norm": 0.0011255062418058515,
1218
+ "learning_rate": 4.426886139579083e-06,
1219
+ "loss": 0.0,
1220
+ "step": 173
1221
+ },
1222
+ {
1223
+ "epoch": 2.4166666666666665,
1224
+ "grad_norm": 0.0010559650836512446,
1225
+ "learning_rate": 4.411727731542937e-06,
1226
+ "loss": 0.0,
1227
+ "step": 174
1228
+ },
1229
+ {
1230
+ "epoch": 2.4305555555555554,
1231
+ "grad_norm": 0.0010468937689438462,
1232
+ "learning_rate": 4.39639814612578e-06,
1233
+ "loss": 0.0,
1234
+ "step": 175
1235
+ },
1236
+ {
1237
+ "epoch": 2.4444444444444446,
1238
+ "grad_norm": 0.0009965520584955812,
1239
+ "learning_rate": 4.3808987559489536e-06,
1240
+ "loss": 0.0,
1241
+ "step": 176
1242
+ },
1243
+ {
1244
+ "epoch": 2.4583333333333335,
1245
+ "grad_norm": 0.000950520858168602,
1246
+ "learning_rate": 4.365230948838232e-06,
1247
+ "loss": 0.0,
1248
+ "step": 177
1249
+ },
1250
+ {
1251
+ "epoch": 2.4722222222222223,
1252
+ "grad_norm": 0.0009662396623753011,
1253
+ "learning_rate": 4.349396127699552e-06,
1254
+ "loss": 0.0,
1255
+ "step": 178
1256
+ },
1257
+ {
1258
+ "epoch": 2.486111111111111,
1259
+ "grad_norm": 0.0009316857904195786,
1260
+ "learning_rate": 4.3333957103934025e-06,
1261
+ "loss": 0.0,
1262
+ "step": 179
1263
+ },
1264
+ {
1265
+ "epoch": 2.5,
1266
+ "grad_norm": 0.0009209261042997241,
1267
+ "learning_rate": 4.317231129607859e-06,
1268
+ "loss": 0.0,
1269
+ "step": 180
1270
+ },
1271
+ {
1272
+ "epoch": 2.513888888888889,
1273
+ "grad_norm": 0.0008661423926241696,
1274
+ "learning_rate": 4.30090383273031e-06,
1275
+ "loss": 0.0,
1276
+ "step": 181
1277
+ },
1278
+ {
1279
+ "epoch": 2.5277777777777777,
1280
+ "grad_norm": 0.0008176359115168452,
1281
+ "learning_rate": 4.2844152817178476e-06,
1282
+ "loss": 0.0,
1283
+ "step": 182
1284
+ },
1285
+ {
1286
+ "epoch": 2.5416666666666665,
1287
+ "grad_norm": 0.0008025923161767423,
1288
+ "learning_rate": 4.267766952966369e-06,
1289
+ "loss": 0.0,
1290
+ "step": 183
1291
+ },
1292
+ {
1293
+ "epoch": 2.5555555555555554,
1294
+ "grad_norm": 0.0008243928314186633,
1295
+ "learning_rate": 4.2509603371783776e-06,
1296
+ "loss": 0.0,
1297
+ "step": 184
1298
+ },
1299
+ {
1300
+ "epoch": 2.5694444444444446,
1301
+ "grad_norm": 0.0013688765466213226,
1302
+ "learning_rate": 4.233996939229502e-06,
1303
+ "loss": 0.0,
1304
+ "step": 185
1305
+ },
1306
+ {
1307
+ "epoch": 2.5833333333333335,
1308
+ "grad_norm": 0.0007681425777263939,
1309
+ "learning_rate": 4.216878278033753e-06,
1310
+ "loss": 0.0,
1311
+ "step": 186
1312
+ },
1313
+ {
1314
+ "epoch": 2.5972222222222223,
1315
+ "grad_norm": 0.0007665084558539093,
1316
+ "learning_rate": 4.199605886407515e-06,
1317
+ "loss": 0.0,
1318
+ "step": 187
1319
+ },
1320
+ {
1321
+ "epoch": 2.611111111111111,
1322
+ "grad_norm": 0.000745179713703692,
1323
+ "learning_rate": 4.1821813109322975e-06,
1324
+ "loss": 0.0,
1325
+ "step": 188
1326
+ },
1327
+ {
1328
+ "epoch": 2.625,
1329
+ "grad_norm": 0.0007080566138029099,
1330
+ "learning_rate": 4.164606111816256e-06,
1331
+ "loss": 0.0,
1332
+ "step": 189
1333
+ },
1334
+ {
1335
+ "epoch": 2.638888888888889,
1336
+ "grad_norm": 0.0007035013986751437,
1337
+ "learning_rate": 4.146881862754485e-06,
1338
+ "loss": 0.0,
1339
+ "step": 190
1340
+ },
1341
+ {
1342
+ "epoch": 2.6527777777777777,
1343
+ "grad_norm": 0.001035734312608838,
1344
+ "learning_rate": 4.129010150788112e-06,
1345
+ "loss": 0.0,
1346
+ "step": 191
1347
+ },
1348
+ {
1349
+ "epoch": 2.6666666666666665,
1350
+ "grad_norm": 0.000686554005369544,
1351
+ "learning_rate": 4.110992576162193e-06,
1352
+ "loss": 0.0,
1353
+ "step": 192
1354
+ },
1355
+ {
1356
+ "epoch": 2.6805555555555554,
1357
+ "grad_norm": 0.0006567820673808455,
1358
+ "learning_rate": 4.092830752182423e-06,
1359
+ "loss": 0.0,
1360
+ "step": 193
1361
+ },
1362
+ {
1363
+ "epoch": 2.6944444444444446,
1364
+ "grad_norm": 0.0006689206347800791,
1365
+ "learning_rate": 4.074526305070679e-06,
1366
+ "loss": 0.0,
1367
+ "step": 194
1368
+ },
1369
+ {
1370
+ "epoch": 2.7083333333333335,
1371
+ "grad_norm": 0.000665506231598556,
1372
+ "learning_rate": 4.056080873819412e-06,
1373
+ "loss": 0.0,
1374
+ "step": 195
1375
+ },
1376
+ {
1377
+ "epoch": 2.7222222222222223,
1378
+ "grad_norm": 0.0006280328962020576,
1379
+ "learning_rate": 4.037496110044885e-06,
1380
+ "loss": 0.0,
1381
+ "step": 196
1382
+ },
1383
+ {
1384
+ "epoch": 2.736111111111111,
1385
+ "grad_norm": 0.0005998269189149141,
1386
+ "learning_rate": 4.018773677839289e-06,
1387
+ "loss": 0.0,
1388
+ "step": 197
1389
+ },
1390
+ {
1391
+ "epoch": 2.75,
1392
+ "grad_norm": 0.0007591253379359841,
1393
+ "learning_rate": 3.999915253621739e-06,
1394
+ "loss": 0.0,
1395
+ "step": 198
1396
+ },
1397
+ {
1398
+ "epoch": 2.763888888888889,
1399
+ "grad_norm": 0.0005739334737882018,
1400
+ "learning_rate": 3.980922525988167e-06,
1401
+ "loss": 0.0,
1402
+ "step": 199
1403
+ },
1404
+ {
1405
+ "epoch": 2.7777777777777777,
1406
+ "grad_norm": 0.0005984510062262416,
1407
+ "learning_rate": 3.961797195560118e-06,
1408
+ "loss": 0.0,
1409
+ "step": 200
1410
+ },
1411
+ {
1412
+ "epoch": 2.7916666666666665,
1413
+ "grad_norm": 0.0007093317108228803,
1414
+ "learning_rate": 3.942540974832486e-06,
1415
+ "loss": 0.0,
1416
+ "step": 201
1417
+ },
1418
+ {
1419
+ "epoch": 2.8055555555555554,
1420
+ "grad_norm": 0.0005686501390300691,
1421
+ "learning_rate": 3.9231555880201655e-06,
1422
+ "loss": 0.0,
1423
+ "step": 202
1424
+ },
1425
+ {
1426
+ "epoch": 2.8194444444444446,
1427
+ "grad_norm": 0.0005396155174821615,
1428
+ "learning_rate": 3.903642770903671e-06,
1429
+ "loss": 0.0,
1430
+ "step": 203
1431
+ },
1432
+ {
1433
+ "epoch": 2.8333333333333335,
1434
+ "grad_norm": 0.000549685733858496,
1435
+ "learning_rate": 3.884004270673711e-06,
1436
+ "loss": 0.0,
1437
+ "step": 204
1438
+ },
1439
+ {
1440
+ "epoch": 2.8472222222222223,
1441
+ "grad_norm": 0.0005211409879848361,
1442
+ "learning_rate": 3.864241845774746e-06,
1443
+ "loss": 0.0,
1444
+ "step": 205
1445
+ },
1446
+ {
1447
+ "epoch": 2.861111111111111,
1448
+ "grad_norm": 0.0005807566340081394,
1449
+ "learning_rate": 3.844357265747531e-06,
1450
+ "loss": 0.0,
1451
+ "step": 206
1452
+ },
1453
+ {
1454
+ "epoch": 2.875,
1455
+ "grad_norm": 0.0005310736014507711,
1456
+ "learning_rate": 3.8243523110706736e-06,
1457
+ "loss": 0.0,
1458
+ "step": 207
1459
+ },
1460
+ {
1461
+ "epoch": 2.888888888888889,
1462
+ "grad_norm": 0.001211474766023457,
1463
+ "learning_rate": 3.8042287730012117e-06,
1464
+ "loss": 0.0,
1465
+ "step": 208
1466
+ },
1467
+ {
1468
+ "epoch": 2.9027777777777777,
1469
+ "grad_norm": 0.0005012262845411897,
1470
+ "learning_rate": 3.7839884534142157e-06,
1471
+ "loss": 0.0,
1472
+ "step": 209
1473
+ },
1474
+ {
1475
+ "epoch": 2.9166666666666665,
1476
+ "grad_norm": 0.0005107534816488624,
1477
+ "learning_rate": 3.7636331646414524e-06,
1478
+ "loss": 0.0,
1479
+ "step": 210
1480
+ },
1481
+ {
1482
+ "epoch": 2.9305555555555554,
1483
+ "grad_norm": 0.0005153871607035398,
1484
+ "learning_rate": 3.7431647293091076e-06,
1485
+ "loss": 0.0,
1486
+ "step": 211
1487
+ },
1488
+ {
1489
+ "epoch": 2.9444444444444446,
1490
+ "grad_norm": 0.0005016613868065178,
1491
+ "learning_rate": 3.7225849801745835e-06,
1492
+ "loss": 0.0,
1493
+ "step": 212
1494
+ },
1495
+ {
1496
+ "epoch": 2.9583333333333335,
1497
+ "grad_norm": 0.00048161958693526685,
1498
+ "learning_rate": 3.701895759962397e-06,
1499
+ "loss": 0.0,
1500
+ "step": 213
1501
+ },
1502
+ {
1503
+ "epoch": 2.9722222222222223,
1504
+ "grad_norm": 0.0004826453805435449,
1505
+ "learning_rate": 3.6810989211991777e-06,
1506
+ "loss": 0.0,
1507
+ "step": 214
1508
+ },
1509
+ {
1510
+ "epoch": 2.986111111111111,
1511
+ "grad_norm": 0.0004991457099094987,
1512
+ "learning_rate": 3.6601963260477923e-06,
1513
+ "loss": 0.0,
1514
+ "step": 215
1515
+ },
1516
+ {
1517
+ "epoch": 3.0,
1518
+ "grad_norm": 0.0004765830235555768,
1519
+ "learning_rate": 3.6391898461406045e-06,
1520
+ "loss": 0.0,
1521
+ "step": 216
1522
+ },
1523
+ {
1524
+ "epoch": 3.013888888888889,
1525
+ "grad_norm": 0.0004497554909903556,
1526
+ "learning_rate": 3.6180813624118898e-06,
1527
+ "loss": 0.0,
1528
+ "step": 217
1529
+ },
1530
+ {
1531
+ "epoch": 3.0277777777777777,
1532
+ "grad_norm": 0.001278965501114726,
1533
+ "learning_rate": 3.5968727649294134e-06,
1534
+ "loss": 0.0,
1535
+ "step": 218
1536
+ },
1537
+ {
1538
+ "epoch": 3.0416666666666665,
1539
+ "grad_norm": 0.00046711499453522265,
1540
+ "learning_rate": 3.575565952725193e-06,
1541
+ "loss": 0.0,
1542
+ "step": 219
1543
+ },
1544
+ {
1545
+ "epoch": 3.0555555555555554,
1546
+ "grad_norm": 0.0004580412060022354,
1547
+ "learning_rate": 3.55416283362546e-06,
1548
+ "loss": 0.0,
1549
+ "step": 220
1550
+ },
1551
+ {
1552
+ "epoch": 3.0694444444444446,
1553
+ "grad_norm": 0.0004473453445825726,
1554
+ "learning_rate": 3.5326653240798283e-06,
1555
+ "loss": 0.0,
1556
+ "step": 221
1557
+ },
1558
+ {
1559
+ "epoch": 3.0833333333333335,
1560
+ "grad_norm": 0.00044585420982912183,
1561
+ "learning_rate": 3.5110753489896924e-06,
1562
+ "loss": 0.0,
1563
+ "step": 222
1564
+ },
1565
+ {
1566
+ "epoch": 3.0972222222222223,
1567
+ "grad_norm": 0.00044625229202210903,
1568
+ "learning_rate": 3.4893948415358803e-06,
1569
+ "loss": 0.0,
1570
+ "step": 223
1571
+ },
1572
+ {
1573
+ "epoch": 3.111111111111111,
1574
+ "grad_norm": 0.00042979326099157333,
1575
+ "learning_rate": 3.4676257430055438e-06,
1576
+ "loss": 0.0,
1577
+ "step": 224
1578
+ },
1579
+ {
1580
+ "epoch": 3.125,
1581
+ "grad_norm": 0.0005280164768919349,
1582
+ "learning_rate": 3.4457700026183378e-06,
1583
+ "loss": 0.0,
1584
+ "step": 225
1585
+ },
1586
+ {
1587
+ "epoch": 3.138888888888889,
1588
+ "grad_norm": 0.0004327085625845939,
1589
+ "learning_rate": 3.4238295773518924e-06,
1590
+ "loss": 0.0,
1591
+ "step": 226
1592
+ },
1593
+ {
1594
+ "epoch": 3.1527777777777777,
1595
+ "grad_norm": 0.0004218154354020953,
1596
+ "learning_rate": 3.4018064317665745e-06,
1597
+ "loss": 0.0,
1598
+ "step": 227
1599
+ },
1600
+ {
1601
+ "epoch": 3.1666666666666665,
1602
+ "grad_norm": 0.0004269857599865645,
1603
+ "learning_rate": 3.3797025378295826e-06,
1604
+ "loss": 0.0,
1605
+ "step": 228
1606
+ },
1607
+ {
1608
+ "epoch": 3.1805555555555554,
1609
+ "grad_norm": 0.0004188821476418525,
1610
+ "learning_rate": 3.357519874738382e-06,
1611
+ "loss": 0.0,
1612
+ "step": 229
1613
+ },
1614
+ {
1615
+ "epoch": 3.1944444444444446,
1616
+ "grad_norm": 0.00043003325117751956,
1617
+ "learning_rate": 3.3352604287434752e-06,
1618
+ "loss": 0.0,
1619
+ "step": 230
1620
+ },
1621
+ {
1622
+ "epoch": 3.2083333333333335,
1623
+ "grad_norm": 0.00041776004945859313,
1624
+ "learning_rate": 3.31292619297056e-06,
1625
+ "loss": 0.0,
1626
+ "step": 231
1627
+ },
1628
+ {
1629
+ "epoch": 3.2222222222222223,
1630
+ "grad_norm": 0.0004131250607315451,
1631
+ "learning_rate": 3.29051916724206e-06,
1632
+ "loss": 0.0,
1633
+ "step": 232
1634
+ },
1635
+ {
1636
+ "epoch": 3.236111111111111,
1637
+ "grad_norm": 0.0004490792634896934,
1638
+ "learning_rate": 3.2680413578980623e-06,
1639
+ "loss": 0.0,
1640
+ "step": 233
1641
+ },
1642
+ {
1643
+ "epoch": 3.25,
1644
+ "grad_norm": 0.00040265225106850266,
1645
+ "learning_rate": 3.245494777616664e-06,
1646
+ "loss": 0.0,
1647
+ "step": 234
1648
+ },
1649
+ {
1650
+ "epoch": 3.263888888888889,
1651
+ "grad_norm": 0.0003899024159181863,
1652
+ "learning_rate": 3.2228814452337587e-06,
1653
+ "loss": 0.0,
1654
+ "step": 235
1655
+ },
1656
+ {
1657
+ "epoch": 3.2777777777777777,
1658
+ "grad_norm": 0.00039753629243932664,
1659
+ "learning_rate": 3.2002033855622683e-06,
1660
+ "loss": 0.0,
1661
+ "step": 236
1662
+ },
1663
+ {
1664
+ "epoch": 3.2916666666666665,
1665
+ "grad_norm": 0.00041745221824385226,
1666
+ "learning_rate": 3.177462629210838e-06,
1667
+ "loss": 0.0,
1668
+ "step": 237
1669
+ },
1670
+ {
1671
+ "epoch": 3.3055555555555554,
1672
+ "grad_norm": 0.00037628141581080854,
1673
+ "learning_rate": 3.154661212402017e-06,
1674
+ "loss": 0.0,
1675
+ "step": 238
1676
+ },
1677
+ {
1678
+ "epoch": 3.3194444444444446,
1679
+ "grad_norm": 0.0004110137524548918,
1680
+ "learning_rate": 3.131801176789934e-06,
1681
+ "loss": 0.0,
1682
+ "step": 239
1683
+ },
1684
+ {
1685
+ "epoch": 3.3333333333333335,
1686
+ "grad_norm": 0.0003878215211443603,
1687
+ "learning_rate": 3.1088845692774798e-06,
1688
+ "loss": 0.0,
1689
+ "step": 240
1690
+ },
1691
+ {
1692
+ "epoch": 3.3472222222222223,
1693
+ "grad_norm": 0.0004746608901768923,
1694
+ "learning_rate": 3.0859134418330373e-06,
1695
+ "loss": 0.0,
1696
+ "step": 241
1697
+ },
1698
+ {
1699
+ "epoch": 3.361111111111111,
1700
+ "grad_norm": 0.0017198650166392326,
1701
+ "learning_rate": 3.0628898513067357e-06,
1702
+ "loss": 0.0,
1703
+ "step": 242
1704
+ },
1705
+ {
1706
+ "epoch": 3.375,
1707
+ "grad_norm": 0.00038812440470792353,
1708
+ "learning_rate": 3.0398158592462847e-06,
1709
+ "loss": 0.0,
1710
+ "step": 243
1711
+ },
1712
+ {
1713
+ "epoch": 3.388888888888889,
1714
+ "grad_norm": 0.0003960718458984047,
1715
+ "learning_rate": 3.0166935317123824e-06,
1716
+ "loss": 0.0,
1717
+ "step": 244
1718
+ },
1719
+ {
1720
+ "epoch": 3.4027777777777777,
1721
+ "grad_norm": 0.0003934325650334358,
1722
+ "learning_rate": 2.9935249390937184e-06,
1723
+ "loss": 0.0,
1724
+ "step": 245
1725
+ },
1726
+ {
1727
+ "epoch": 3.4166666666666665,
1728
+ "grad_norm": 0.0003809865447692573,
1729
+ "learning_rate": 2.970312155921585e-06,
1730
+ "loss": 0.0,
1731
+ "step": 246
1732
+ },
1733
+ {
1734
+ "epoch": 3.4305555555555554,
1735
+ "grad_norm": 0.0003733540652319789,
1736
+ "learning_rate": 2.9470572606841295e-06,
1737
+ "loss": 0.0,
1738
+ "step": 247
1739
+ },
1740
+ {
1741
+ "epoch": 3.4444444444444446,
1742
+ "grad_norm": 0.0007575592026114464,
1743
+ "learning_rate": 2.9237623356402423e-06,
1744
+ "loss": 0.0,
1745
+ "step": 248
1746
+ },
1747
+ {
1748
+ "epoch": 3.4583333333333335,
1749
+ "grad_norm": 0.0003538963501341641,
1750
+ "learning_rate": 2.900429466633107e-06,
1751
+ "loss": 0.0,
1752
+ "step": 249
1753
+ },
1754
+ {
1755
+ "epoch": 3.4722222222222223,
1756
+ "grad_norm": 0.00036024293513037264,
1757
+ "learning_rate": 2.8770607429034352e-06,
1758
+ "loss": 0.0,
1759
+ "step": 250
1760
+ },
1761
+ {
1762
+ "epoch": 3.486111111111111,
1763
+ "grad_norm": 0.0003511797694955021,
1764
+ "learning_rate": 2.8536582569023964e-06,
1765
+ "loss": 0.0,
1766
+ "step": 251
1767
+ },
1768
+ {
1769
+ "epoch": 3.5,
1770
+ "grad_norm": 0.00034679597592912614,
1771
+ "learning_rate": 2.8302241041042564e-06,
1772
+ "loss": 0.0,
1773
+ "step": 252
1774
+ },
1775
+ {
1776
+ "epoch": 3.513888888888889,
1777
+ "grad_norm": 0.00037080422043800354,
1778
+ "learning_rate": 2.8067603828187446e-06,
1779
+ "loss": 0.0,
1780
+ "step": 253
1781
+ },
1782
+ {
1783
+ "epoch": 3.5277777777777777,
1784
+ "grad_norm": 0.0003417868574615568,
1785
+ "learning_rate": 2.7832691940031755e-06,
1786
+ "loss": 0.0,
1787
+ "step": 254
1788
+ },
1789
+ {
1790
+ "epoch": 3.5416666666666665,
1791
+ "grad_norm": 0.00034637749195098877,
1792
+ "learning_rate": 2.759752641074322e-06,
1793
+ "loss": 0.0,
1794
+ "step": 255
1795
+ },
1796
+ {
1797
+ "epoch": 3.5555555555555554,
1798
+ "grad_norm": 0.00035772964474745095,
1799
+ "learning_rate": 2.7362128297200784e-06,
1800
+ "loss": 0.0,
1801
+ "step": 256
1802
+ },
1803
+ {
1804
+ "epoch": 3.5694444444444446,
1805
+ "grad_norm": 0.00034110111300833523,
1806
+ "learning_rate": 2.712651867710914e-06,
1807
+ "loss": 0.0,
1808
+ "step": 257
1809
+ },
1810
+ {
1811
+ "epoch": 3.5833333333333335,
1812
+ "grad_norm": 0.00033183529740199447,
1813
+ "learning_rate": 2.6890718647111424e-06,
1814
+ "loss": 0.0,
1815
+ "step": 258
1816
+ },
1817
+ {
1818
+ "epoch": 3.5972222222222223,
1819
+ "grad_norm": 0.00034375995164737105,
1820
+ "learning_rate": 2.665474932090017e-06,
1821
+ "loss": 0.0,
1822
+ "step": 259
1823
+ },
1824
+ {
1825
+ "epoch": 3.611111111111111,
1826
+ "grad_norm": 0.0003534927382133901,
1827
+ "learning_rate": 2.6418631827326857e-06,
1828
+ "loss": 0.0,
1829
+ "step": 260
1830
+ },
1831
+ {
1832
+ "epoch": 3.625,
1833
+ "grad_norm": 0.00034480984322726727,
1834
+ "learning_rate": 2.6182387308509927e-06,
1835
+ "loss": 0.0,
1836
+ "step": 261
1837
+ },
1838
+ {
1839
+ "epoch": 3.638888888888889,
1840
+ "grad_norm": 0.00034357619006186724,
1841
+ "learning_rate": 2.5946036917941765e-06,
1842
+ "loss": 0.0,
1843
+ "step": 262
1844
+ },
1845
+ {
1846
+ "epoch": 3.6527777777777777,
1847
+ "grad_norm": 0.0003348125028423965,
1848
+ "learning_rate": 2.570960181859458e-06,
1849
+ "loss": 0.0,
1850
+ "step": 263
1851
+ },
1852
+ {
1853
+ "epoch": 3.6666666666666665,
1854
+ "grad_norm": 0.0003396561951376498,
1855
+ "learning_rate": 2.547310318102548e-06,
1856
+ "loss": 0.0,
1857
+ "step": 264
1858
+ },
1859
+ {
1860
+ "epoch": 3.6805555555555554,
1861
+ "grad_norm": 0.000327035115333274,
1862
+ "learning_rate": 2.5236562181480794e-06,
1863
+ "loss": 0.0,
1864
+ "step": 265
1865
+ },
1866
+ {
1867
+ "epoch": 3.6944444444444446,
1868
+ "grad_norm": 0.0012853932566940784,
1869
+ "learning_rate": 2.5e-06,
1870
+ "loss": 0.0,
1871
+ "step": 266
1872
+ },
1873
+ {
1874
+ "epoch": 3.7083333333333335,
1875
+ "grad_norm": 0.00033309016725979745,
1876
+ "learning_rate": 2.4763437818519205e-06,
1877
+ "loss": 0.0,
1878
+ "step": 267
1879
+ },
1880
+ {
1881
+ "epoch": 3.7222222222222223,
1882
+ "grad_norm": 0.0003192981530446559,
1883
+ "learning_rate": 2.4526896818974534e-06,
1884
+ "loss": 0.0,
1885
+ "step": 268
1886
+ },
1887
+ {
1888
+ "epoch": 3.736111111111111,
1889
+ "grad_norm": 0.00032640976132825017,
1890
+ "learning_rate": 2.429039818140543e-06,
1891
+ "loss": 0.0,
1892
+ "step": 269
1893
+ },
1894
+ {
1895
+ "epoch": 3.75,
1896
+ "grad_norm": 0.00033392352634109557,
1897
+ "learning_rate": 2.405396308205825e-06,
1898
+ "loss": 0.0,
1899
+ "step": 270
1900
+ },
1901
+ {
1902
+ "epoch": 3.763888888888889,
1903
+ "grad_norm": 0.0003594683366827667,
1904
+ "learning_rate": 2.381761269149009e-06,
1905
+ "loss": 0.0,
1906
+ "step": 271
1907
+ },
1908
+ {
1909
+ "epoch": 3.7777777777777777,
1910
+ "grad_norm": 0.010392317548394203,
1911
+ "learning_rate": 2.358136817267315e-06,
1912
+ "loss": 0.0,
1913
+ "step": 272
1914
+ },
1915
+ {
1916
+ "epoch": 3.7916666666666665,
1917
+ "grad_norm": 0.00031630549347028136,
1918
+ "learning_rate": 2.334525067909983e-06,
1919
+ "loss": 0.0,
1920
+ "step": 273
1921
+ },
1922
+ {
1923
+ "epoch": 3.8055555555555554,
1924
+ "grad_norm": 0.0003196642210241407,
1925
+ "learning_rate": 2.3109281352888593e-06,
1926
+ "loss": 0.0,
1927
+ "step": 274
1928
+ },
1929
+ {
1930
+ "epoch": 3.8194444444444446,
1931
+ "grad_norm": 0.00031541771022602916,
1932
+ "learning_rate": 2.2873481322890866e-06,
1933
+ "loss": 0.0,
1934
+ "step": 275
1935
+ },
1936
+ {
1937
+ "epoch": 3.8333333333333335,
1938
+ "grad_norm": 0.0003151163400616497,
1939
+ "learning_rate": 2.263787170279922e-06,
1940
+ "loss": 0.0,
1941
+ "step": 276
1942
+ },
1943
+ {
1944
+ "epoch": 3.8472222222222223,
1945
+ "grad_norm": 0.0003220181097276509,
1946
+ "learning_rate": 2.2402473589256793e-06,
1947
+ "loss": 0.0,
1948
+ "step": 277
1949
+ },
1950
+ {
1951
+ "epoch": 3.861111111111111,
1952
+ "grad_norm": 0.00031665421556681395,
1953
+ "learning_rate": 2.2167308059968258e-06,
1954
+ "loss": 0.0,
1955
+ "step": 278
1956
+ },
1957
+ {
1958
+ "epoch": 3.875,
1959
+ "grad_norm": 0.0003038264694623649,
1960
+ "learning_rate": 2.193239617181256e-06,
1961
+ "loss": 0.0,
1962
+ "step": 279
1963
+ },
1964
+ {
1965
+ "epoch": 3.888888888888889,
1966
+ "grad_norm": 0.00031601826776750386,
1967
+ "learning_rate": 2.169775895895745e-06,
1968
+ "loss": 0.0,
1969
+ "step": 280
1970
+ },
1971
+ {
1972
+ "epoch": 3.9027777777777777,
1973
+ "grad_norm": 0.0003112203849013895,
1974
+ "learning_rate": 2.146341743097604e-06,
1975
+ "loss": 0.0,
1976
+ "step": 281
1977
+ },
1978
+ {
1979
+ "epoch": 3.9166666666666665,
1980
+ "grad_norm": 0.00030921402503736317,
1981
+ "learning_rate": 2.1229392570965656e-06,
1982
+ "loss": 0.0,
1983
+ "step": 282
1984
+ },
1985
+ {
1986
+ "epoch": 3.9305555555555554,
1987
+ "grad_norm": 0.00031801871955394745,
1988
+ "learning_rate": 2.0995705333668948e-06,
1989
+ "loss": 0.0,
1990
+ "step": 283
1991
+ },
1992
+ {
1993
+ "epoch": 3.9444444444444446,
1994
+ "grad_norm": 0.0003068145888391882,
1995
+ "learning_rate": 2.0762376643597586e-06,
1996
+ "loss": 0.0,
1997
+ "step": 284
1998
+ },
1999
+ {
2000
+ "epoch": 3.9583333333333335,
2001
+ "grad_norm": 0.000303666980471462,
2002
+ "learning_rate": 2.0529427393158704e-06,
2003
+ "loss": 0.0,
2004
+ "step": 285
2005
+ },
2006
+ {
2007
+ "epoch": 3.9722222222222223,
2008
+ "grad_norm": 0.00037687006988562644,
2009
+ "learning_rate": 2.0296878440784164e-06,
2010
+ "loss": 0.0,
2011
+ "step": 286
2012
+ },
2013
+ {
2014
+ "epoch": 3.986111111111111,
2015
+ "grad_norm": 0.0004179875541012734,
2016
+ "learning_rate": 2.006475060906283e-06,
2017
+ "loss": 0.0,
2018
+ "step": 287
2019
+ },
2020
+ {
2021
+ "epoch": 4.0,
2022
+ "grad_norm": 0.00030332262394949794,
2023
+ "learning_rate": 1.9833064682876175e-06,
2024
+ "loss": 0.0,
2025
+ "step": 288
2026
+ },
2027
+ {
2028
+ "epoch": 4.013888888888889,
2029
+ "grad_norm": 0.000312824355205521,
2030
+ "learning_rate": 1.9601841407537157e-06,
2031
+ "loss": 0.0,
2032
+ "step": 289
2033
+ },
2034
+ {
2035
+ "epoch": 4.027777777777778,
2036
+ "grad_norm": 0.0008900280809029937,
2037
+ "learning_rate": 1.937110148693265e-06,
2038
+ "loss": 0.0,
2039
+ "step": 290
2040
+ },
2041
+ {
2042
+ "epoch": 4.041666666666667,
2043
+ "grad_norm": 0.00030201984918676317,
2044
+ "learning_rate": 1.9140865581669627e-06,
2045
+ "loss": 0.0,
2046
+ "step": 291
2047
+ },
2048
+ {
2049
+ "epoch": 4.055555555555555,
2050
+ "grad_norm": 0.00037866891943849623,
2051
+ "learning_rate": 1.8911154307225204e-06,
2052
+ "loss": 0.0,
2053
+ "step": 292
2054
+ },
2055
+ {
2056
+ "epoch": 4.069444444444445,
2057
+ "grad_norm": 0.0003057627473026514,
2058
+ "learning_rate": 1.8681988232100674e-06,
2059
+ "loss": 0.0,
2060
+ "step": 293
2061
+ },
2062
+ {
2063
+ "epoch": 4.083333333333333,
2064
+ "grad_norm": 0.0003006605838891119,
2065
+ "learning_rate": 1.8453387875979834e-06,
2066
+ "loss": 0.0,
2067
+ "step": 294
2068
+ },
2069
+ {
2070
+ "epoch": 4.097222222222222,
2071
+ "grad_norm": 0.0003039598523173481,
2072
+ "learning_rate": 1.822537370789163e-06,
2073
+ "loss": 0.0,
2074
+ "step": 295
2075
+ },
2076
+ {
2077
+ "epoch": 4.111111111111111,
2078
+ "grad_norm": 0.00030075316317379475,
2079
+ "learning_rate": 1.7997966144377328e-06,
2080
+ "loss": 0.0,
2081
+ "step": 296
2082
+ },
2083
+ {
2084
+ "epoch": 4.125,
2085
+ "grad_norm": 0.0005559928831644356,
2086
+ "learning_rate": 1.7771185547662417e-06,
2087
+ "loss": 0.0,
2088
+ "step": 297
2089
+ },
2090
+ {
2091
+ "epoch": 4.138888888888889,
2092
+ "grad_norm": 0.0003315582871437073,
2093
+ "learning_rate": 1.754505222383337e-06,
2094
+ "loss": 0.0,
2095
+ "step": 298
2096
+ },
2097
+ {
2098
+ "epoch": 4.152777777777778,
2099
+ "grad_norm": 0.00028943977667950094,
2100
+ "learning_rate": 1.7319586421019383e-06,
2101
+ "loss": 0.0,
2102
+ "step": 299
2103
+ },
2104
+ {
2105
+ "epoch": 4.166666666666667,
2106
+ "grad_norm": 0.0003514060808811337,
2107
+ "learning_rate": 1.7094808327579401e-06,
2108
+ "loss": 0.0,
2109
+ "step": 300
2110
+ },
2111
+ {
2112
+ "epoch": 4.180555555555555,
2113
+ "grad_norm": 0.00029012124286964536,
2114
+ "learning_rate": 1.6870738070294412e-06,
2115
+ "loss": 0.0,
2116
+ "step": 301
2117
+ },
2118
+ {
2119
+ "epoch": 4.194444444444445,
2120
+ "grad_norm": 0.000285898830043152,
2121
+ "learning_rate": 1.6647395712565256e-06,
2122
+ "loss": 0.0,
2123
+ "step": 302
2124
+ },
2125
+ {
2126
+ "epoch": 4.208333333333333,
2127
+ "grad_norm": 0.0002975537208840251,
2128
+ "learning_rate": 1.6424801252616186e-06,
2129
+ "loss": 0.0,
2130
+ "step": 303
2131
+ },
2132
+ {
2133
+ "epoch": 4.222222222222222,
2134
+ "grad_norm": 0.00029446210828609765,
2135
+ "learning_rate": 1.6202974621704176e-06,
2136
+ "loss": 0.0,
2137
+ "step": 304
2138
+ },
2139
+ {
2140
+ "epoch": 4.236111111111111,
2141
+ "grad_norm": 0.0002837205829564482,
2142
+ "learning_rate": 1.5981935682334266e-06,
2143
+ "loss": 0.0,
2144
+ "step": 305
2145
+ },
2146
+ {
2147
+ "epoch": 4.25,
2148
+ "grad_norm": 0.0002935337251983583,
2149
+ "learning_rate": 1.5761704226481078e-06,
2150
+ "loss": 0.0,
2151
+ "step": 306
2152
+ },
2153
+ {
2154
+ "epoch": 4.263888888888889,
2155
+ "grad_norm": 0.00029275196720846,
2156
+ "learning_rate": 1.5542299973816626e-06,
2157
+ "loss": 0.0,
2158
+ "step": 307
2159
+ },
2160
+ {
2161
+ "epoch": 4.277777777777778,
2162
+ "grad_norm": 0.00029929872835054994,
2163
+ "learning_rate": 1.5323742569944573e-06,
2164
+ "loss": 0.0,
2165
+ "step": 308
2166
+ },
2167
+ {
2168
+ "epoch": 4.291666666666667,
2169
+ "grad_norm": 0.00028991978615522385,
2170
+ "learning_rate": 1.5106051584641208e-06,
2171
+ "loss": 0.0,
2172
+ "step": 309
2173
+ },
2174
+ {
2175
+ "epoch": 4.305555555555555,
2176
+ "grad_norm": 0.0002811246959026903,
2177
+ "learning_rate": 1.4889246510103078e-06,
2178
+ "loss": 0.0,
2179
+ "step": 310
2180
+ },
2181
+ {
2182
+ "epoch": 4.319444444444445,
2183
+ "grad_norm": 0.00028082230710424483,
2184
+ "learning_rate": 1.4673346759201728e-06,
2185
+ "loss": 0.0,
2186
+ "step": 311
2187
+ },
2188
+ {
2189
+ "epoch": 4.333333333333333,
2190
+ "grad_norm": 0.0002810833975672722,
2191
+ "learning_rate": 1.44583716637454e-06,
2192
+ "loss": 0.0,
2193
+ "step": 312
2194
+ },
2195
+ {
2196
+ "epoch": 4.347222222222222,
2197
+ "grad_norm": 0.00030640949262306094,
2198
+ "learning_rate": 1.4244340472748076e-06,
2199
+ "loss": 0.0,
2200
+ "step": 313
2201
+ },
2202
+ {
2203
+ "epoch": 4.361111111111111,
2204
+ "grad_norm": 0.00027884720475412905,
2205
+ "learning_rate": 1.403127235070587e-06,
2206
+ "loss": 0.0,
2207
+ "step": 314
2208
+ },
2209
+ {
2210
+ "epoch": 4.375,
2211
+ "grad_norm": 0.00028082833159714937,
2212
+ "learning_rate": 1.381918637588112e-06,
2213
+ "loss": 0.0,
2214
+ "step": 315
2215
+ },
2216
+ {
2217
+ "epoch": 4.388888888888889,
2218
+ "grad_norm": 0.00028363679302856326,
2219
+ "learning_rate": 1.3608101538593965e-06,
2220
+ "loss": 0.0,
2221
+ "step": 316
2222
+ },
2223
+ {
2224
+ "epoch": 4.402777777777778,
2225
+ "grad_norm": 0.00027668694383464754,
2226
+ "learning_rate": 1.3398036739522088e-06,
2227
+ "loss": 0.0,
2228
+ "step": 317
2229
+ },
2230
+ {
2231
+ "epoch": 4.416666666666667,
2232
+ "grad_norm": 0.00028155132895335555,
2233
+ "learning_rate": 1.3189010788008234e-06,
2234
+ "loss": 0.0,
2235
+ "step": 318
2236
+ },
2237
+ {
2238
+ "epoch": 4.430555555555555,
2239
+ "grad_norm": 0.0007724284077994525,
2240
+ "learning_rate": 1.2981042400376032e-06,
2241
+ "loss": 0.0,
2242
+ "step": 319
2243
+ },
2244
+ {
2245
+ "epoch": 4.444444444444445,
2246
+ "grad_norm": 0.00036324880784377456,
2247
+ "learning_rate": 1.277415019825417e-06,
2248
+ "loss": 0.0,
2249
+ "step": 320
2250
+ },
2251
+ {
2252
+ "epoch": 4.458333333333333,
2253
+ "grad_norm": 0.00027311878511682153,
2254
+ "learning_rate": 1.2568352706908937e-06,
2255
+ "loss": 0.0,
2256
+ "step": 321
2257
+ },
2258
+ {
2259
+ "epoch": 4.472222222222222,
2260
+ "grad_norm": 0.0002935140219051391,
2261
+ "learning_rate": 1.2363668353585486e-06,
2262
+ "loss": 0.0,
2263
+ "step": 322
2264
+ },
2265
+ {
2266
+ "epoch": 4.486111111111111,
2267
+ "grad_norm": 0.0002762887452263385,
2268
+ "learning_rate": 1.216011546585785e-06,
2269
+ "loss": 0.0,
2270
+ "step": 323
2271
+ },
2272
+ {
2273
+ "epoch": 4.5,
2274
+ "grad_norm": 0.00029656346305273473,
2275
+ "learning_rate": 1.195771226998789e-06,
2276
+ "loss": 0.0,
2277
+ "step": 324
2278
+ },
2279
+ {
2280
+ "epoch": 4.513888888888889,
2281
+ "grad_norm": 0.0002801907539833337,
2282
+ "learning_rate": 1.1756476889293269e-06,
2283
+ "loss": 0.0,
2284
+ "step": 325
2285
+ },
2286
+ {
2287
+ "epoch": 4.527777777777778,
2288
+ "grad_norm": 0.0002702914352994412,
2289
+ "learning_rate": 1.1556427342524698e-06,
2290
+ "loss": 0.0,
2291
+ "step": 326
2292
+ },
2293
+ {
2294
+ "epoch": 4.541666666666667,
2295
+ "grad_norm": 0.0002727097016759217,
2296
+ "learning_rate": 1.1357581542252555e-06,
2297
+ "loss": 0.0,
2298
+ "step": 327
2299
+ },
2300
+ {
2301
+ "epoch": 4.555555555555555,
2302
+ "grad_norm": 0.0002765726239886135,
2303
+ "learning_rate": 1.1159957293262888e-06,
2304
+ "loss": 0.0,
2305
+ "step": 328
2306
+ },
2307
+ {
2308
+ "epoch": 4.569444444444445,
2309
+ "grad_norm": 0.0002687490778043866,
2310
+ "learning_rate": 1.0963572290963298e-06,
2311
+ "loss": 0.0,
2312
+ "step": 329
2313
+ },
2314
+ {
2315
+ "epoch": 4.583333333333333,
2316
+ "grad_norm": 0.0002718923205975443,
2317
+ "learning_rate": 1.0768444119798357e-06,
2318
+ "loss": 0.0,
2319
+ "step": 330
2320
+ },
2321
+ {
2322
+ "epoch": 4.597222222222222,
2323
+ "grad_norm": 0.0003026482881978154,
2324
+ "learning_rate": 1.0574590251675145e-06,
2325
+ "loss": 0.0,
2326
+ "step": 331
2327
+ },
2328
+ {
2329
+ "epoch": 4.611111111111111,
2330
+ "grad_norm": 0.00027299264911562204,
2331
+ "learning_rate": 1.0382028044398823e-06,
2332
+ "loss": 0.0,
2333
+ "step": 332
2334
+ },
2335
+ {
2336
+ "epoch": 4.625,
2337
+ "grad_norm": 0.00026989809703081846,
2338
+ "learning_rate": 1.0190774740118343e-06,
2339
+ "loss": 0.0,
2340
+ "step": 333
2341
+ },
2342
+ {
2343
+ "epoch": 4.638888888888889,
2344
+ "grad_norm": 0.00028061502962373197,
2345
+ "learning_rate": 1.0000847463782615e-06,
2346
+ "loss": 0.0,
2347
+ "step": 334
2348
+ },
2349
+ {
2350
+ "epoch": 4.652777777777778,
2351
+ "grad_norm": 0.0002712835557758808,
2352
+ "learning_rate": 9.812263221607114e-07,
2353
+ "loss": 0.0,
2354
+ "step": 335
2355
+ },
2356
+ {
2357
+ "epoch": 4.666666666666667,
2358
+ "grad_norm": 0.0002652051334735006,
2359
+ "learning_rate": 9.625038899551162e-07,
2360
+ "loss": 0.0,
2361
+ "step": 336
2362
+ },
2363
+ {
2364
+ "epoch": 4.680555555555555,
2365
+ "grad_norm": 0.00044494643225334585,
2366
+ "learning_rate": 9.439191261805894e-07,
2367
+ "loss": 0.0,
2368
+ "step": 337
2369
+ },
2370
+ {
2371
+ "epoch": 4.694444444444445,
2372
+ "grad_norm": 0.00026834887103177607,
2373
+ "learning_rate": 9.254736949293216e-07,
2374
+ "loss": 0.0,
2375
+ "step": 338
2376
+ },
2377
+ {
2378
+ "epoch": 4.708333333333333,
2379
+ "grad_norm": 0.00030554624390788376,
2380
+ "learning_rate": 9.07169247817579e-07,
2381
+ "loss": 0.0,
2382
+ "step": 339
2383
+ },
2384
+ {
2385
+ "epoch": 4.722222222222222,
2386
+ "grad_norm": 0.00027393290656618774,
2387
+ "learning_rate": 8.890074238378074e-07,
2388
+ "loss": 0.0,
2389
+ "step": 340
2390
+ },
2391
+ {
2392
+ "epoch": 4.736111111111111,
2393
+ "grad_norm": 0.0012748402077704668,
2394
+ "learning_rate": 8.709898492118885e-07,
2395
+ "loss": 0.0,
2396
+ "step": 341
2397
+ },
2398
+ {
2399
+ "epoch": 4.75,
2400
+ "grad_norm": 0.0002683771017473191,
2401
+ "learning_rate": 8.531181372455161e-07,
2402
+ "loss": 0.0,
2403
+ "step": 342
2404
+ },
2405
+ {
2406
+ "epoch": 4.763888888888889,
2407
+ "grad_norm": 0.0002686232910491526,
2408
+ "learning_rate": 8.353938881837445e-07,
2409
+ "loss": 0.0,
2410
+ "step": 343
2411
+ },
2412
+ {
2413
+ "epoch": 4.777777777777778,
2414
+ "grad_norm": 0.0002642960462253541,
2415
+ "learning_rate": 8.178186890677029e-07,
2416
+ "loss": 0.0,
2417
+ "step": 344
2418
+ },
2419
+ {
2420
+ "epoch": 4.791666666666667,
2421
+ "grad_norm": 0.00026234518736600876,
2422
+ "learning_rate": 8.003941135924859e-07,
2423
+ "loss": 0.0,
2424
+ "step": 345
2425
+ },
2426
+ {
2427
+ "epoch": 4.805555555555555,
2428
+ "grad_norm": 0.0002638711594045162,
2429
+ "learning_rate": 7.83121721966248e-07,
2430
+ "loss": 0.0,
2431
+ "step": 346
2432
+ },
2433
+ {
2434
+ "epoch": 4.819444444444445,
2435
+ "grad_norm": 0.00038043910171836615,
2436
+ "learning_rate": 7.66003060770498e-07,
2437
+ "loss": 0.0,
2438
+ "step": 347
2439
+ },
2440
+ {
2441
+ "epoch": 4.833333333333333,
2442
+ "grad_norm": 0.00027849708567373455,
2443
+ "learning_rate": 7.490396628216237e-07,
2444
+ "loss": 0.0,
2445
+ "step": 348
2446
+ },
2447
+ {
2448
+ "epoch": 4.847222222222222,
2449
+ "grad_norm": 0.00026442529633641243,
2450
+ "learning_rate": 7.322330470336314e-07,
2451
+ "loss": 0.0,
2452
+ "step": 349
2453
+ },
2454
+ {
2455
+ "epoch": 4.861111111111111,
2456
+ "grad_norm": 0.0002640223829075694,
2457
+ "learning_rate": 7.155847182821524e-07,
2458
+ "loss": 0.0,
2459
+ "step": 350
2460
+ },
2461
+ {
2462
+ "epoch": 4.875,
2463
+ "grad_norm": 0.0002679000608623028,
2464
+ "learning_rate": 6.990961672696908e-07,
2465
+ "loss": 0.0,
2466
+ "step": 351
2467
+ },
2468
+ {
2469
+ "epoch": 4.888888888888889,
2470
+ "grad_norm": 0.0003060480812564492,
2471
+ "learning_rate": 6.827688703921407e-07,
2472
+ "loss": 0.0,
2473
+ "step": 352
2474
+ },
2475
+ {
2476
+ "epoch": 4.902777777777778,
2477
+ "grad_norm": 0.0002725216909311712,
2478
+ "learning_rate": 6.666042896065983e-07,
2479
+ "loss": 0.0,
2480
+ "step": 353
2481
+ },
2482
+ {
2483
+ "epoch": 4.916666666666667,
2484
+ "grad_norm": 0.0007128149154596031,
2485
+ "learning_rate": 6.506038723004484e-07,
2486
+ "loss": 0.0,
2487
+ "step": 354
2488
+ },
2489
+ {
2490
+ "epoch": 4.930555555555555,
2491
+ "grad_norm": 0.0003282964462414384,
2492
+ "learning_rate": 6.347690511617693e-07,
2493
+ "loss": 0.0,
2494
+ "step": 355
2495
+ },
2496
+ {
2497
+ "epoch": 4.944444444444445,
2498
+ "grad_norm": 0.00026580950361676514,
2499
+ "learning_rate": 6.191012440510469e-07,
2500
+ "loss": 0.0,
2501
+ "step": 356
2502
+ },
2503
+ {
2504
+ "epoch": 4.958333333333333,
2505
+ "grad_norm": 0.0002644002088345587,
2506
+ "learning_rate": 6.036018538742208e-07,
2507
+ "loss": 0.0,
2508
+ "step": 357
2509
+ },
2510
+ {
2511
+ "epoch": 4.972222222222222,
2512
+ "grad_norm": 0.0002604973560664803,
2513
+ "learning_rate": 5.882722684570638e-07,
2514
+ "loss": 0.0,
2515
+ "step": 358
2516
+ },
2517
+ {
2518
+ "epoch": 4.986111111111111,
2519
+ "grad_norm": 0.0002634973789099604,
2520
+ "learning_rate": 5.731138604209169e-07,
2521
+ "loss": 0.0,
2522
+ "step": 359
2523
+ },
2524
+ {
2525
+ "epoch": 5.0,
2526
+ "grad_norm": 0.00026600516866892576,
2527
+ "learning_rate": 5.581279870597866e-07,
2528
+ "loss": 0.0,
2529
+ "step": 360
2530
+ },
2531
+ {
2532
+ "epoch": 5.013888888888889,
2533
+ "grad_norm": 0.0002706224622670561,
2534
+ "learning_rate": 5.433159902188043e-07,
2535
+ "loss": 0.0,
2536
+ "step": 361
2537
+ },
2538
+ {
2539
+ "epoch": 5.027777777777778,
2540
+ "grad_norm": 0.00026735506253317,
2541
+ "learning_rate": 5.286791961740855e-07,
2542
+ "loss": 0.0,
2543
+ "step": 362
2544
+ },
2545
+ {
2546
+ "epoch": 5.041666666666667,
2547
+ "grad_norm": 0.00026590144261717796,
2548
+ "learning_rate": 5.142189155139685e-07,
2549
+ "loss": 0.0,
2550
+ "step": 363
2551
+ },
2552
+ {
2553
+ "epoch": 5.055555555555555,
2554
+ "grad_norm": 0.0002626982459332794,
2555
+ "learning_rate": 4.999364430216639e-07,
2556
+ "loss": 0.0,
2557
+ "step": 364
2558
+ },
2559
+ {
2560
+ "epoch": 5.069444444444445,
2561
+ "grad_norm": 0.0002645182830747217,
2562
+ "learning_rate": 4.85833057559322e-07,
2563
+ "loss": 0.0,
2564
+ "step": 365
2565
+ },
2566
+ {
2567
+ "epoch": 5.083333333333333,
2568
+ "grad_norm": 0.00033136035199277103,
2569
+ "learning_rate": 4.719100219535194e-07,
2570
+ "loss": 0.0,
2571
+ "step": 366
2572
+ },
2573
+ {
2574
+ "epoch": 5.097222222222222,
2575
+ "grad_norm": 0.0002559632412157953,
2576
+ "learning_rate": 4.581685828821858e-07,
2577
+ "loss": 0.0,
2578
+ "step": 367
2579
+ },
2580
+ {
2581
+ "epoch": 5.111111111111111,
2582
+ "grad_norm": 0.0002641724713612348,
2583
+ "learning_rate": 4.4460997076297504e-07,
2584
+ "loss": 0.0,
2585
+ "step": 368
2586
+ },
2587
+ {
2588
+ "epoch": 5.125,
2589
+ "grad_norm": 0.00025784719036892056,
2590
+ "learning_rate": 4.3123539964309486e-07,
2591
+ "loss": 0.0,
2592
+ "step": 369
2593
+ },
2594
+ {
2595
+ "epoch": 5.138888888888889,
2596
+ "grad_norm": 0.00025356386322528124,
2597
+ "learning_rate": 4.180460670905978e-07,
2598
+ "loss": 0.0,
2599
+ "step": 370
2600
+ },
2601
+ {
2602
+ "epoch": 5.152777777777778,
2603
+ "grad_norm": 0.00033126556081697345,
2604
+ "learning_rate": 4.0504315408714993e-07,
2605
+ "loss": 0.0,
2606
+ "step": 371
2607
+ },
2608
+ {
2609
+ "epoch": 5.166666666666667,
2610
+ "grad_norm": 0.00025866623036563396,
2611
+ "learning_rate": 3.922278249222894e-07,
2612
+ "loss": 0.0,
2613
+ "step": 372
2614
+ },
2615
+ {
2616
+ "epoch": 5.180555555555555,
2617
+ "grad_norm": 0.00026357153546996415,
2618
+ "learning_rate": 3.796012270891672e-07,
2619
+ "loss": 0.0,
2620
+ "step": 373
2621
+ },
2622
+ {
2623
+ "epoch": 5.194444444444445,
2624
+ "grad_norm": 0.00026371076819486916,
2625
+ "learning_rate": 3.671644911818084e-07,
2626
+ "loss": 0.0,
2627
+ "step": 374
2628
+ },
2629
+ {
2630
+ "epoch": 5.208333333333333,
2631
+ "grad_norm": 0.0015637637116014957,
2632
+ "learning_rate": 3.549187307938726e-07,
2633
+ "loss": 0.0,
2634
+ "step": 375
2635
+ },
2636
+ {
2637
+ "epoch": 5.222222222222222,
2638
+ "grad_norm": 0.0002598503197077662,
2639
+ "learning_rate": 3.4286504241894283e-07,
2640
+ "loss": 0.0,
2641
+ "step": 376
2642
+ },
2643
+ {
2644
+ "epoch": 5.236111111111111,
2645
+ "grad_norm": 0.0002642101899255067,
2646
+ "learning_rate": 3.310045053523475e-07,
2647
+ "loss": 0.0,
2648
+ "step": 377
2649
+ },
2650
+ {
2651
+ "epoch": 5.25,
2652
+ "grad_norm": 0.0002549289492890239,
2653
+ "learning_rate": 3.1933818159451566e-07,
2654
+ "loss": 0.0,
2655
+ "step": 378
2656
+ },
2657
+ {
2658
+ "epoch": 5.263888888888889,
2659
+ "grad_norm": 0.00025667273439466953,
2660
+ "learning_rate": 3.078671157558877e-07,
2661
+ "loss": 0.0,
2662
+ "step": 379
2663
+ },
2664
+ {
2665
+ "epoch": 5.277777777777778,
2666
+ "grad_norm": 0.00026106147561222315,
2667
+ "learning_rate": 2.965923349633779e-07,
2668
+ "loss": 0.0,
2669
+ "step": 380
2670
+ },
2671
+ {
2672
+ "epoch": 5.291666666666667,
2673
+ "grad_norm": 0.0002968902699649334,
2674
+ "learning_rate": 2.8551484876840815e-07,
2675
+ "loss": 0.0,
2676
+ "step": 381
2677
+ },
2678
+ {
2679
+ "epoch": 5.305555555555555,
2680
+ "grad_norm": 0.00035064725670963526,
2681
+ "learning_rate": 2.7463564905650855e-07,
2682
+ "loss": 0.0,
2683
+ "step": 382
2684
+ },
2685
+ {
2686
+ "epoch": 5.319444444444445,
2687
+ "grad_norm": 0.00025268958415836096,
2688
+ "learning_rate": 2.639557099585047e-07,
2689
+ "loss": 0.0,
2690
+ "step": 383
2691
+ },
2692
+ {
2693
+ "epoch": 5.333333333333333,
2694
+ "grad_norm": 0.0002559676067903638,
2695
+ "learning_rate": 2.53475987763295e-07,
2696
+ "loss": 0.0,
2697
+ "step": 384
2698
+ },
2699
+ {
2700
+ "epoch": 5.347222222222222,
2701
+ "grad_norm": 0.00026469549629837275,
2702
+ "learning_rate": 2.431974208322191e-07,
2703
+ "loss": 0.0,
2704
+ "step": 385
2705
+ },
2706
+ {
2707
+ "epoch": 5.361111111111111,
2708
+ "grad_norm": 0.00034869826049543917,
2709
+ "learning_rate": 2.3312092951504357e-07,
2710
+ "loss": 0.0,
2711
+ "step": 386
2712
+ },
2713
+ {
2714
+ "epoch": 5.375,
2715
+ "grad_norm": 0.00025658466620370746,
2716
+ "learning_rate": 2.2324741606754629e-07,
2717
+ "loss": 0.0,
2718
+ "step": 387
2719
+ },
2720
+ {
2721
+ "epoch": 5.388888888888889,
2722
+ "grad_norm": 0.00026476720813661814,
2723
+ "learning_rate": 2.135777645707318e-07,
2724
+ "loss": 0.0,
2725
+ "step": 388
2726
+ },
2727
+ {
2728
+ "epoch": 5.402777777777778,
2729
+ "grad_norm": 0.00025239703245460987,
2730
+ "learning_rate": 2.041128408516696e-07,
2731
+ "loss": 0.0,
2732
+ "step": 389
2733
+ },
2734
+ {
2735
+ "epoch": 5.416666666666667,
2736
+ "grad_norm": 0.00025563855888321996,
2737
+ "learning_rate": 1.9485349240596613e-07,
2738
+ "loss": 0.0,
2739
+ "step": 390
2740
+ },
2741
+ {
2742
+ "epoch": 5.430555555555555,
2743
+ "grad_norm": 0.0002565851900726557,
2744
+ "learning_rate": 1.8580054832188055e-07,
2745
+ "loss": 0.0,
2746
+ "step": 391
2747
+ },
2748
+ {
2749
+ "epoch": 5.444444444444445,
2750
+ "grad_norm": 0.00026290182722732425,
2751
+ "learning_rate": 1.7695481920608716e-07,
2752
+ "loss": 0.0,
2753
+ "step": 392
2754
+ },
2755
+ {
2756
+ "epoch": 5.458333333333333,
2757
+ "grad_norm": 0.0002583847672212869,
2758
+ "learning_rate": 1.683170971110934e-07,
2759
+ "loss": 0.0,
2760
+ "step": 393
2761
+ },
2762
+ {
2763
+ "epoch": 5.472222222222222,
2764
+ "grad_norm": 0.00034513280843384564,
2765
+ "learning_rate": 1.5988815546431807e-07,
2766
+ "loss": 0.0,
2767
+ "step": 394
2768
+ },
2769
+ {
2770
+ "epoch": 5.486111111111111,
2771
+ "grad_norm": 0.0002678663295228034,
2772
+ "learning_rate": 1.5166874899884054e-07,
2773
+ "loss": 0.0,
2774
+ "step": 395
2775
+ },
2776
+ {
2777
+ "epoch": 5.5,
2778
+ "grad_norm": 0.0002519397239666432,
2779
+ "learning_rate": 1.4365961368581844e-07,
2780
+ "loss": 0.0,
2781
+ "step": 396
2782
+ },
2783
+ {
2784
+ "epoch": 5.513888888888889,
2785
+ "grad_norm": 0.0003545888757798821,
2786
+ "learning_rate": 1.3586146666858923e-07,
2787
+ "loss": 0.0,
2788
+ "step": 397
2789
+ },
2790
+ {
2791
+ "epoch": 5.527777777777778,
2792
+ "grad_norm": 0.0002581175649538636,
2793
+ "learning_rate": 1.2827500619845918e-07,
2794
+ "loss": 0.0,
2795
+ "step": 398
2796
+ },
2797
+ {
2798
+ "epoch": 5.541666666666667,
2799
+ "grad_norm": 0.0002705502265598625,
2800
+ "learning_rate": 1.2090091157217653e-07,
2801
+ "loss": 0.0,
2802
+ "step": 399
2803
+ },
2804
+ {
2805
+ "epoch": 5.555555555555555,
2806
+ "grad_norm": 0.0005023585399612784,
2807
+ "learning_rate": 1.137398430711123e-07,
2808
+ "loss": 0.0,
2809
+ "step": 400
2810
+ },
2811
+ {
2812
+ "epoch": 5.569444444444445,
2813
+ "grad_norm": 0.0002529410703573376,
2814
+ "learning_rate": 1.0679244190213378e-07,
2815
+ "loss": 0.0,
2816
+ "step": 401
2817
+ },
2818
+ {
2819
+ "epoch": 5.583333333333333,
2820
+ "grad_norm": 0.0002479004324413836,
2821
+ "learning_rate": 1.0005933014019309e-07,
2822
+ "loss": 0.0,
2823
+ "step": 402
2824
+ },
2825
+ {
2826
+ "epoch": 5.597222222222222,
2827
+ "grad_norm": 0.0008182842284440994,
2828
+ "learning_rate": 9.354111067262584e-08,
2829
+ "loss": 0.0,
2830
+ "step": 403
2831
+ },
2832
+ {
2833
+ "epoch": 5.611111111111111,
2834
+ "grad_norm": 0.0002645702043082565,
2835
+ "learning_rate": 8.723836714516681e-08,
2836
+ "loss": 0.0,
2837
+ "step": 404
2838
+ },
2839
+ {
2840
+ "epoch": 5.625,
2841
+ "grad_norm": 0.00040876964339986444,
2842
+ "learning_rate": 8.115166390969126e-08,
2843
+ "loss": 0.0,
2844
+ "step": 405
2845
+ },
2846
+ {
2847
+ "epoch": 5.638888888888889,
2848
+ "grad_norm": 0.0003426918410696089,
2849
+ "learning_rate": 7.528154597368192e-08,
2850
+ "loss": 0.0,
2851
+ "step": 406
2852
+ },
2853
+ {
2854
+ "epoch": 5.652777777777778,
2855
+ "grad_norm": 0.00025878456654027104,
2856
+ "learning_rate": 6.962853895142924e-08,
2857
+ "loss": 0.0,
2858
+ "step": 407
2859
+ },
2860
+ {
2861
+ "epoch": 5.666666666666667,
2862
+ "grad_norm": 0.00025401037419214845,
2863
+ "learning_rate": 6.419314901696671e-08,
2864
+ "loss": 0.0,
2865
+ "step": 408
2866
+ },
2867
+ {
2868
+ "epoch": 5.680555555555555,
2869
+ "grad_norm": 0.0002544631715863943,
2870
+ "learning_rate": 5.897586285874751e-08,
2871
+ "loss": 0.0,
2872
+ "step": 409
2873
+ },
2874
+ {
2875
+ "epoch": 5.694444444444445,
2876
+ "grad_norm": 0.0002563282323535532,
2877
+ "learning_rate": 5.3977147636068425e-08,
2878
+ "loss": 0.0,
2879
+ "step": 410
2880
+ },
2881
+ {
2882
+ "epoch": 5.708333333333333,
2883
+ "grad_norm": 0.0002564689493738115,
2884
+ "learning_rate": 4.919745093723588e-08,
2885
+ "loss": 0.0,
2886
+ "step": 411
2887
+ },
2888
+ {
2889
+ "epoch": 5.722222222222222,
2890
+ "grad_norm": 0.0002686359512154013,
2891
+ "learning_rate": 4.4637200739493514e-08,
2892
+ "loss": 0.0,
2893
+ "step": 412
2894
+ },
2895
+ {
2896
+ "epoch": 5.736111111111111,
2897
+ "grad_norm": 0.00024789239978417754,
2898
+ "learning_rate": 4.0296805370696466e-08,
2899
+ "loss": 0.0,
2900
+ "step": 413
2901
+ },
2902
+ {
2903
+ "epoch": 5.75,
2904
+ "grad_norm": 0.00029518938390538096,
2905
+ "learning_rate": 3.617665347275201e-08,
2906
+ "loss": 0.0,
2907
+ "step": 414
2908
+ },
2909
+ {
2910
+ "epoch": 5.763888888888889,
2911
+ "grad_norm": 0.0002470539475325495,
2912
+ "learning_rate": 3.227711396682015e-08,
2913
+ "loss": 0.0,
2914
+ "step": 415
2915
+ },
2916
+ {
2917
+ "epoch": 5.777777777777778,
2918
+ "grad_norm": 0.0002557995612733066,
2919
+ "learning_rate": 2.8598536020278678e-08,
2920
+ "loss": 0.0,
2921
+ "step": 416
2922
+ },
2923
+ {
2924
+ "epoch": 5.791666666666667,
2925
+ "grad_norm": 0.00028313451912254095,
2926
+ "learning_rate": 2.5141249015459833e-08,
2927
+ "loss": 0.0,
2928
+ "step": 417
2929
+ },
2930
+ {
2931
+ "epoch": 5.805555555555555,
2932
+ "grad_norm": 0.00026003815582953393,
2933
+ "learning_rate": 2.1905562520156686e-08,
2934
+ "loss": 0.0,
2935
+ "step": 418
2936
+ },
2937
+ {
2938
+ "epoch": 5.819444444444445,
2939
+ "grad_norm": 0.0002526485186535865,
2940
+ "learning_rate": 1.8891766259904188e-08,
2941
+ "loss": 0.0,
2942
+ "step": 419
2943
+ },
2944
+ {
2945
+ "epoch": 5.833333333333333,
2946
+ "grad_norm": 0.0002612722455523908,
2947
+ "learning_rate": 1.6100130092037704e-08,
2948
+ "loss": 0.0,
2949
+ "step": 420
2950
+ },
2951
+ {
2952
+ "epoch": 5.847222222222222,
2953
+ "grad_norm": 0.00026318017626181245,
2954
+ "learning_rate": 1.3530903981528454e-08,
2955
+ "loss": 0.0,
2956
+ "step": 421
2957
+ },
2958
+ {
2959
+ "epoch": 5.861111111111111,
2960
+ "grad_norm": 0.0002644322521518916,
2961
+ "learning_rate": 1.118431797860281e-08,
2962
+ "loss": 0.0,
2963
+ "step": 422
2964
+ },
2965
+ {
2966
+ "epoch": 5.875,
2967
+ "grad_norm": 0.00025975541211664677,
2968
+ "learning_rate": 9.060582198141822e-09,
2969
+ "loss": 0.0,
2970
+ "step": 423
2971
+ },
2972
+ {
2973
+ "epoch": 5.888888888888889,
2974
+ "grad_norm": 0.0002580354339443147,
2975
+ "learning_rate": 7.159886800869875e-09,
2976
+ "loss": 0.0,
2977
+ "step": 424
2978
+ },
2979
+ {
2980
+ "epoch": 5.902777777777778,
2981
+ "grad_norm": 0.0002680405741557479,
2982
+ "learning_rate": 5.482401976325269e-09,
2983
+ "loss": 0.0,
2984
+ "step": 425
2985
+ },
2986
+ {
2987
+ "epoch": 5.916666666666667,
2988
+ "grad_norm": 0.00026338655152358115,
2989
+ "learning_rate": 4.028277927621838e-09,
2990
+ "loss": 0.0,
2991
+ "step": 426
2992
+ },
2993
+ {
2994
+ "epoch": 5.930555555555555,
2995
+ "grad_norm": 0.0002724181395024061,
2996
+ "learning_rate": 2.7976448580008252e-09,
2997
+ "loss": 0.0,
2998
+ "step": 427
2999
+ },
3000
+ {
3001
+ "epoch": 5.944444444444445,
3002
+ "grad_norm": 0.0002537508844397962,
3003
+ "learning_rate": 1.7906129591713228e-09,
3004
+ "loss": 0.0,
3005
+ "step": 428
3006
+ },
3007
+ {
3008
+ "epoch": 5.958333333333333,
3009
+ "grad_norm": 0.0002590265648905188,
3010
+ "learning_rate": 1.0072724014437153e-09,
3011
+ "loss": 0.0,
3012
+ "step": 429
3013
+ },
3014
+ {
3015
+ "epoch": 5.972222222222222,
3016
+ "grad_norm": 0.0002608827780932188,
3017
+ "learning_rate": 4.476933256555849e-10,
3018
+ "loss": 0.0,
3019
+ "step": 430
3020
+ },
3021
+ {
3022
+ "epoch": 5.986111111111111,
3023
+ "grad_norm": 0.000258398154983297,
3024
+ "learning_rate": 1.1192583689256797e-10,
3025
+ "loss": 0.0,
3026
+ "step": 431
3027
+ },
3028
+ {
3029
+ "epoch": 6.0,
3030
+ "grad_norm": 0.0008098710095509887,
3031
+ "learning_rate": 0.0,
3032
+ "loss": 0.0,
3033
+ "step": 432
3034
+ }
3035
+ ],
3036
+ "logging_steps": 1,
3037
+ "max_steps": 432,
3038
+ "num_input_tokens_seen": 0,
3039
+ "num_train_epochs": 6,
3040
+ "save_steps": 72,
3041
+ "stateful_callbacks": {
3042
+ "TrainerControl": {
3043
+ "args": {
3044
+ "should_epoch_stop": false,
3045
+ "should_evaluate": false,
3046
+ "should_log": false,
3047
+ "should_save": true,
3048
+ "should_training_stop": true
3049
+ },
3050
+ "attributes": {}
3051
+ }
3052
+ },
3053
+ "total_flos": 1.0878798040714445e+18,
3054
+ "train_batch_size": 4,
3055
+ "trial_name": null,
3056
+ "trial_params": null
3057
+ }
checkpoint-432/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c4a21cce8e23b70f0a541e7503c799ab823dd5a615b154bf086ba44af0edeef6
3
+ size 7992
checkpoint-432/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)