Volko76 commited on
Commit
4202234
1 Parent(s): 24b0b45

Upload folder using huggingface_hub

Browse files
Files changed (41) hide show
  1. README.md +140 -1
  2. adapter_config.json +34 -0
  3. adapter_model.bin +3 -0
  4. added_tokens.json +5 -0
  5. checkpoint-13105/README.md +202 -0
  6. checkpoint-13105/adapter_config.json +34 -0
  7. checkpoint-13105/adapter_model.safetensors +3 -0
  8. checkpoint-13105/added_tokens.json +5 -0
  9. checkpoint-13105/merges.txt +0 -0
  10. checkpoint-13105/optimizer.pt +3 -0
  11. checkpoint-13105/rng_state.pth +3 -0
  12. checkpoint-13105/scheduler.pt +3 -0
  13. checkpoint-13105/special_tokens_map.json +20 -0
  14. checkpoint-13105/tokenizer.json +0 -0
  15. checkpoint-13105/tokenizer_config.json +43 -0
  16. checkpoint-13105/trainer_state.json +0 -0
  17. checkpoint-13105/training_args.bin +3 -0
  18. checkpoint-13105/vocab.json +0 -0
  19. checkpoint-475/README.md +202 -0
  20. checkpoint-475/adapter_config.json +34 -0
  21. checkpoint-475/adapter_model.safetensors +3 -0
  22. checkpoint-475/added_tokens.json +5 -0
  23. checkpoint-475/merges.txt +0 -0
  24. checkpoint-475/optimizer.pt +3 -0
  25. checkpoint-475/rng_state.pth +3 -0
  26. checkpoint-475/scheduler.pt +3 -0
  27. checkpoint-475/special_tokens_map.json +20 -0
  28. checkpoint-475/tokenizer.json +0 -0
  29. checkpoint-475/tokenizer_config.json +43 -0
  30. checkpoint-475/trainer_state.json +3378 -0
  31. checkpoint-475/training_args.bin +3 -0
  32. checkpoint-475/vocab.json +0 -0
  33. config.json +42 -0
  34. merges.txt +0 -0
  35. runs/Apr11_16-32-20_volko-MS-7D09/events.out.tfevents.1712845940.volko-MS-7D09.38265.0 +3 -0
  36. runs/Apr11_16-53-26_volko-MS-7D09/events.out.tfevents.1712847206.volko-MS-7D09.40309.0 +3 -0
  37. runs/Apr11_17-04-13_volko-MS-7D09/events.out.tfevents.1712847853.volko-MS-7D09.41247.0 +3 -0
  38. special_tokens_map.json +20 -0
  39. tokenizer.json +0 -0
  40. tokenizer_config.json +43 -0
  41. vocab.json +0 -0
README.md CHANGED
@@ -1,3 +1,142 @@
1
  ---
2
- license: apache-2.0
 
 
 
 
 
 
 
3
  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
  ---
2
+ license: other
3
+ library_name: peft
4
+ tags:
5
+ - generated_from_trainer
6
+ base_model: Qwen/Qwen1.5-0.5B
7
+ model-index:
8
+ - name: lora-out
9
+ results: []
10
  ---
11
+
12
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
13
+ should probably proofread and complete it, then remove this comment. -->
14
+
15
+ [<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
16
+ <details><summary>See axolotl config</summary>
17
+
18
+ axolotl version: `0.4.0`
19
+ ```yaml
20
+ base_model: Qwen/Qwen1.5-0.5B
21
+ model_type: AutoModelForCausalLM
22
+ tokenizer_type: AutoTokenizer
23
+
24
+ trust_remote_code: true
25
+
26
+ load_in_8bit: true
27
+ load_in_4bit: false
28
+ strict: false
29
+
30
+ datasets:
31
+ - path: jpacifico/French-Alpaca-dataset-Instruct-55K
32
+ type: alpaca
33
+ dataset_prepared_path:
34
+ val_set_size: 0.05
35
+ output_dir: ./lora-out
36
+
37
+ sequence_len: 2048 # supports up to 8192
38
+ sample_packing: false
39
+ pad_to_sequence_len:
40
+
41
+ adapter: lora
42
+ lora_model_dir:
43
+ lora_r: 32
44
+ lora_alpha: 16
45
+ lora_dropout: 0.05
46
+ lora_target_linear: true
47
+ lora_fan_in_fan_out:
48
+
49
+ wandb_project:
50
+ wandb_entity:
51
+ wandb_watch:
52
+ wandb_name:
53
+ wandb_log_model:
54
+
55
+ gradient_accumulation_steps: 4
56
+ micro_batch_size: 1
57
+ num_epochs: 1
58
+ optimizer: adamw_bnb_8bit
59
+ lr_scheduler: cosine
60
+ learning_rate: 0.0002
61
+
62
+ train_on_inputs: false
63
+ group_by_length: false
64
+ bf16: auto
65
+ fp16:
66
+ tf32: false
67
+
68
+ gradient_checkpointing: false
69
+ early_stopping_patience:
70
+ resume_from_checkpoint:
71
+ local_rank:
72
+ logging_steps: 1
73
+ xformers_attention:
74
+ flash_attention:
75
+
76
+ warmup_steps: 10
77
+ evals_per_epoch: 4
78
+ eval_table_size:
79
+ eval_max_new_tokens: 128
80
+ saves_per_epoch: 1
81
+ debug:
82
+ deepspeed:
83
+ weight_decay: 0.0
84
+ fsdp:
85
+ fsdp_config:
86
+ special_tokens:
87
+
88
+ ```
89
+
90
+ </details><br>
91
+
92
+ # lora-out
93
+
94
+ This model is a fine-tuned version of [Qwen/Qwen1.5-0.5B](https://huggingface.co/Qwen/Qwen1.5-0.5B) on the None dataset.
95
+ It achieves the following results on the evaluation set:
96
+ - Loss: nan
97
+
98
+ ## Model description
99
+
100
+ More information needed
101
+
102
+ ## Intended uses & limitations
103
+
104
+ More information needed
105
+
106
+ ## Training and evaluation data
107
+
108
+ More information needed
109
+
110
+ ## Training procedure
111
+
112
+ ### Training hyperparameters
113
+
114
+ The following hyperparameters were used during training:
115
+ - learning_rate: 0.0002
116
+ - train_batch_size: 1
117
+ - eval_batch_size: 1
118
+ - seed: 42
119
+ - gradient_accumulation_steps: 4
120
+ - total_train_batch_size: 4
121
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
122
+ - lr_scheduler_type: cosine
123
+ - lr_scheduler_warmup_steps: 10
124
+ - num_epochs: 1
125
+
126
+ ### Training results
127
+
128
+ | Training Loss | Epoch | Step | Validation Loss |
129
+ |:-------------:|:-----:|:----:|:---------------:|
130
+ | 1.4213 | 0.0 | 1 | nan |
131
+ | 1.0472 | 0.25 | 3277 | nan |
132
+ | 1.4289 | 0.5 | 6554 | nan |
133
+ | 1.6165 | 0.75 | 9831 | nan |
134
+
135
+
136
+ ### Framework versions
137
+
138
+ - PEFT 0.10.0
139
+ - Transformers 4.40.0.dev0
140
+ - Pytorch 2.2.2
141
+ - Datasets 2.18.0
142
+ - Tokenizers 0.15.0
adapter_config.json ADDED
@@ -0,0 +1,34 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "Qwen/Qwen1.5-0.5B",
5
+ "bias": "none",
6
+ "fan_in_fan_out": null,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 16,
14
+ "lora_dropout": 0.05,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 32,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "o_proj",
24
+ "v_proj",
25
+ "gate_proj",
26
+ "down_proj",
27
+ "k_proj",
28
+ "q_proj",
29
+ "up_proj"
30
+ ],
31
+ "task_type": "CAUSAL_LM",
32
+ "use_dora": false,
33
+ "use_rslora": false
34
+ }
adapter_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:807088491fc73daa7477d675f55c710b05b829d1ce2927d1f0b1e102a0264c23
3
+ size 60676170
added_tokens.json ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+ {
2
+ "<|endoftext|>": 151643,
3
+ "<|im_end|>": 151645,
4
+ "<|im_start|>": 151644
5
+ }
checkpoint-13105/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ base_model: Qwen/Qwen1.5-0.5B
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 0.10.0
checkpoint-13105/adapter_config.json ADDED
@@ -0,0 +1,34 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "Qwen/Qwen1.5-0.5B",
5
+ "bias": "none",
6
+ "fan_in_fan_out": null,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 16,
14
+ "lora_dropout": 0.05,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 32,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "o_proj",
24
+ "v_proj",
25
+ "gate_proj",
26
+ "down_proj",
27
+ "k_proj",
28
+ "q_proj",
29
+ "up_proj"
30
+ ],
31
+ "task_type": "CAUSAL_LM",
32
+ "use_dora": false,
33
+ "use_rslora": false
34
+ }
checkpoint-13105/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:8e14394f034d36a1e0688b1db8e5e1eda1f4423fe8ed4a81e678e11adf138382
3
+ size 60599872
checkpoint-13105/added_tokens.json ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+ {
2
+ "<|endoftext|>": 151643,
3
+ "<|im_end|>": 151645,
4
+ "<|im_start|>": 151644
5
+ }
checkpoint-13105/merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-13105/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b73d2dc75c8b2bf0784a6c801bd52b2a187b7d13405a5b08b529cb25fd184a6e
3
+ size 30723092
checkpoint-13105/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:3366175c7f29ead4afc790d73217f0ac8231cc0f95b982c050b5022478b06fe4
3
+ size 14244
checkpoint-13105/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e74e7ce9fb51bebfdcf8be91b516547c1f38df077a815b3fe8b31c66169dda21
3
+ size 1064
checkpoint-13105/special_tokens_map.json ADDED
@@ -0,0 +1,20 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "additional_special_tokens": [
3
+ "<|im_start|>",
4
+ "<|im_end|>"
5
+ ],
6
+ "eos_token": {
7
+ "content": "<|endoftext|>",
8
+ "lstrip": false,
9
+ "normalized": false,
10
+ "rstrip": false,
11
+ "single_word": false
12
+ },
13
+ "pad_token": {
14
+ "content": "<|endoftext|>",
15
+ "lstrip": false,
16
+ "normalized": false,
17
+ "rstrip": false,
18
+ "single_word": false
19
+ }
20
+ }
checkpoint-13105/tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-13105/tokenizer_config.json ADDED
@@ -0,0 +1,43 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_prefix_space": false,
3
+ "added_tokens_decoder": {
4
+ "151643": {
5
+ "content": "<|endoftext|>",
6
+ "lstrip": false,
7
+ "normalized": false,
8
+ "rstrip": false,
9
+ "single_word": false,
10
+ "special": true
11
+ },
12
+ "151644": {
13
+ "content": "<|im_start|>",
14
+ "lstrip": false,
15
+ "normalized": false,
16
+ "rstrip": false,
17
+ "single_word": false,
18
+ "special": true
19
+ },
20
+ "151645": {
21
+ "content": "<|im_end|>",
22
+ "lstrip": false,
23
+ "normalized": false,
24
+ "rstrip": false,
25
+ "single_word": false,
26
+ "special": true
27
+ }
28
+ },
29
+ "additional_special_tokens": [
30
+ "<|im_start|>",
31
+ "<|im_end|>"
32
+ ],
33
+ "bos_token": null,
34
+ "chat_template": "{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system\nYou are a helpful assistant<|im_end|>\n' }}{% endif %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
35
+ "clean_up_tokenization_spaces": false,
36
+ "eos_token": "<|endoftext|>",
37
+ "errors": "replace",
38
+ "model_max_length": 32768,
39
+ "pad_token": "<|endoftext|>",
40
+ "split_special_tokens": false,
41
+ "tokenizer_class": "Qwen2Tokenizer",
42
+ "unk_token": null
43
+ }
checkpoint-13105/trainer_state.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-13105/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b3f3fad28a028c0f2db58dd0e98057fd1f6d6f14fd12149fd7997f77062ceb2a
3
+ size 5752
checkpoint-13105/vocab.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-475/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ base_model: Qwen/Qwen1.5-0.5B
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 0.10.0
checkpoint-475/adapter_config.json ADDED
@@ -0,0 +1,34 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "Qwen/Qwen1.5-0.5B",
5
+ "bias": "none",
6
+ "fan_in_fan_out": null,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 16,
14
+ "lora_dropout": 0.05,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 32,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "gate_proj",
24
+ "down_proj",
25
+ "o_proj",
26
+ "up_proj",
27
+ "v_proj",
28
+ "q_proj",
29
+ "k_proj"
30
+ ],
31
+ "task_type": "CAUSAL_LM",
32
+ "use_dora": false,
33
+ "use_rslora": false
34
+ }
checkpoint-475/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:54b3e967b729f742e1ab902d55c9f10641ebe9f2695aa58d13efe40c3b54f6bc
3
+ size 60599872
checkpoint-475/added_tokens.json ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+ {
2
+ "<|endoftext|>": 151643,
3
+ "<|im_end|>": 151645,
4
+ "<|im_start|>": 151644
5
+ }
checkpoint-475/merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-475/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c5c70a89c6440b79ff52bcc3586a2b8b901f33f0b3a9694856d1c4b6e2fa125d
3
+ size 30723092
checkpoint-475/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:abeaf8862616c21f7b62fcd82983987d9d6a5df087a0f3263981a478e87dab0e
3
+ size 14244
checkpoint-475/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5d3ab8b8dc5babc32b4adc3c596b50dd0fcac27b238d3838d86c3c68054c541d
3
+ size 1064
checkpoint-475/special_tokens_map.json ADDED
@@ -0,0 +1,20 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "additional_special_tokens": [
3
+ "<|im_start|>",
4
+ "<|im_end|>"
5
+ ],
6
+ "eos_token": {
7
+ "content": "<|endoftext|>",
8
+ "lstrip": false,
9
+ "normalized": false,
10
+ "rstrip": false,
11
+ "single_word": false
12
+ },
13
+ "pad_token": {
14
+ "content": "<|endoftext|>",
15
+ "lstrip": false,
16
+ "normalized": false,
17
+ "rstrip": false,
18
+ "single_word": false
19
+ }
20
+ }
checkpoint-475/tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-475/tokenizer_config.json ADDED
@@ -0,0 +1,43 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_prefix_space": false,
3
+ "added_tokens_decoder": {
4
+ "151643": {
5
+ "content": "<|endoftext|>",
6
+ "lstrip": false,
7
+ "normalized": false,
8
+ "rstrip": false,
9
+ "single_word": false,
10
+ "special": true
11
+ },
12
+ "151644": {
13
+ "content": "<|im_start|>",
14
+ "lstrip": false,
15
+ "normalized": false,
16
+ "rstrip": false,
17
+ "single_word": false,
18
+ "special": true
19
+ },
20
+ "151645": {
21
+ "content": "<|im_end|>",
22
+ "lstrip": false,
23
+ "normalized": false,
24
+ "rstrip": false,
25
+ "single_word": false,
26
+ "special": true
27
+ }
28
+ },
29
+ "additional_special_tokens": [
30
+ "<|im_start|>",
31
+ "<|im_end|>"
32
+ ],
33
+ "bos_token": null,
34
+ "chat_template": "{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system\nYou are a helpful assistant<|im_end|>\n' }}{% endif %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
35
+ "clean_up_tokenization_spaces": false,
36
+ "eos_token": "<|endoftext|>",
37
+ "errors": "replace",
38
+ "model_max_length": 32768,
39
+ "pad_token": "<|endoftext|>",
40
+ "split_special_tokens": false,
41
+ "tokenizer_class": "Qwen2Tokenizer",
42
+ "unk_token": null
43
+ }
checkpoint-475/trainer_state.json ADDED
@@ -0,0 +1,3378 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": null,
3
+ "best_model_checkpoint": null,
4
+ "epoch": 1.0,
5
+ "eval_steps": 119,
6
+ "global_step": 475,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.0,
13
+ "grad_norm": 0.7395525574684143,
14
+ "learning_rate": 2e-05,
15
+ "loss": 1.1916,
16
+ "step": 1
17
+ },
18
+ {
19
+ "epoch": 0.0,
20
+ "eval_loss": 1.3024712800979614,
21
+ "eval_runtime": 11.3342,
22
+ "eval_samples_per_second": 8.823,
23
+ "eval_steps_per_second": 8.823,
24
+ "step": 1
25
+ },
26
+ {
27
+ "epoch": 0.0,
28
+ "grad_norm": 0.7760837078094482,
29
+ "learning_rate": 4e-05,
30
+ "loss": 1.5154,
31
+ "step": 2
32
+ },
33
+ {
34
+ "epoch": 0.01,
35
+ "grad_norm": 1.630995512008667,
36
+ "learning_rate": 6e-05,
37
+ "loss": 2.1425,
38
+ "step": 3
39
+ },
40
+ {
41
+ "epoch": 0.01,
42
+ "grad_norm": 0.6175426244735718,
43
+ "learning_rate": 8e-05,
44
+ "loss": 0.7877,
45
+ "step": 4
46
+ },
47
+ {
48
+ "epoch": 0.01,
49
+ "grad_norm": 0.5972404479980469,
50
+ "learning_rate": 0.0001,
51
+ "loss": 1.3798,
52
+ "step": 5
53
+ },
54
+ {
55
+ "epoch": 0.01,
56
+ "grad_norm": 0.5723439455032349,
57
+ "learning_rate": 0.00012,
58
+ "loss": 1.0747,
59
+ "step": 6
60
+ },
61
+ {
62
+ "epoch": 0.01,
63
+ "grad_norm": 1.4761886596679688,
64
+ "learning_rate": 0.00014,
65
+ "loss": 1.1005,
66
+ "step": 7
67
+ },
68
+ {
69
+ "epoch": 0.02,
70
+ "grad_norm": 1.2958413362503052,
71
+ "learning_rate": 0.00016,
72
+ "loss": 1.1242,
73
+ "step": 8
74
+ },
75
+ {
76
+ "epoch": 0.02,
77
+ "grad_norm": 0.9850685000419617,
78
+ "learning_rate": 0.00018,
79
+ "loss": 1.1449,
80
+ "step": 9
81
+ },
82
+ {
83
+ "epoch": 0.02,
84
+ "grad_norm": 1.666906714439392,
85
+ "learning_rate": 0.0002,
86
+ "loss": 1.4931,
87
+ "step": 10
88
+ },
89
+ {
90
+ "epoch": 0.02,
91
+ "grad_norm": 0.5160439014434814,
92
+ "learning_rate": 0.00019999771775537991,
93
+ "loss": 1.1436,
94
+ "step": 11
95
+ },
96
+ {
97
+ "epoch": 0.03,
98
+ "grad_norm": 1.0970433950424194,
99
+ "learning_rate": 0.00019999087112569246,
100
+ "loss": 1.6171,
101
+ "step": 12
102
+ },
103
+ {
104
+ "epoch": 0.03,
105
+ "grad_norm": 0.7956830263137817,
106
+ "learning_rate": 0.00019997946042345127,
107
+ "loss": 1.3005,
108
+ "step": 13
109
+ },
110
+ {
111
+ "epoch": 0.03,
112
+ "grad_norm": 1.2406549453735352,
113
+ "learning_rate": 0.00019996348616949672,
114
+ "loss": 1.6621,
115
+ "step": 14
116
+ },
117
+ {
118
+ "epoch": 0.03,
119
+ "grad_norm": 0.932831346988678,
120
+ "learning_rate": 0.0001999429490929718,
121
+ "loss": 1.784,
122
+ "step": 15
123
+ },
124
+ {
125
+ "epoch": 0.03,
126
+ "grad_norm": 0.9084440469741821,
127
+ "learning_rate": 0.00019991785013128923,
128
+ "loss": 1.5638,
129
+ "step": 16
130
+ },
131
+ {
132
+ "epoch": 0.04,
133
+ "grad_norm": 1.491622805595398,
134
+ "learning_rate": 0.0001998881904300884,
135
+ "loss": 1.5091,
136
+ "step": 17
137
+ },
138
+ {
139
+ "epoch": 0.04,
140
+ "grad_norm": 0.6921408176422119,
141
+ "learning_rate": 0.00019985397134318319,
142
+ "loss": 0.9959,
143
+ "step": 18
144
+ },
145
+ {
146
+ "epoch": 0.04,
147
+ "grad_norm": 1.7786202430725098,
148
+ "learning_rate": 0.0001998151944325001,
149
+ "loss": 1.0953,
150
+ "step": 19
151
+ },
152
+ {
153
+ "epoch": 0.04,
154
+ "grad_norm": 0.5404906272888184,
155
+ "learning_rate": 0.00019977186146800707,
156
+ "loss": 2.0195,
157
+ "step": 20
158
+ },
159
+ {
160
+ "epoch": 0.04,
161
+ "grad_norm": 1.5230717658996582,
162
+ "learning_rate": 0.00019972397442763262,
163
+ "loss": 1.0865,
164
+ "step": 21
165
+ },
166
+ {
167
+ "epoch": 0.05,
168
+ "grad_norm": 6.9937639236450195,
169
+ "learning_rate": 0.00019967153549717553,
170
+ "loss": 1.6098,
171
+ "step": 22
172
+ },
173
+ {
174
+ "epoch": 0.05,
175
+ "grad_norm": 0.6447493433952332,
176
+ "learning_rate": 0.00019961454707020514,
177
+ "loss": 1.63,
178
+ "step": 23
179
+ },
180
+ {
181
+ "epoch": 0.05,
182
+ "grad_norm": 0.5249179601669312,
183
+ "learning_rate": 0.00019955301174795208,
184
+ "loss": 0.9971,
185
+ "step": 24
186
+ },
187
+ {
188
+ "epoch": 0.05,
189
+ "grad_norm": 1.7006235122680664,
190
+ "learning_rate": 0.00019948693233918952,
191
+ "loss": 1.151,
192
+ "step": 25
193
+ },
194
+ {
195
+ "epoch": 0.05,
196
+ "grad_norm": 1.094476580619812,
197
+ "learning_rate": 0.00019941631186010494,
198
+ "loss": 1.0216,
199
+ "step": 26
200
+ },
201
+ {
202
+ "epoch": 0.06,
203
+ "grad_norm": 0.7347458004951477,
204
+ "learning_rate": 0.0001993411535341625,
205
+ "loss": 0.8214,
206
+ "step": 27
207
+ },
208
+ {
209
+ "epoch": 0.06,
210
+ "grad_norm": 0.36545494198799133,
211
+ "learning_rate": 0.00019926146079195594,
212
+ "loss": 1.3825,
213
+ "step": 28
214
+ },
215
+ {
216
+ "epoch": 0.06,
217
+ "grad_norm": 1.0544871091842651,
218
+ "learning_rate": 0.0001991772372710519,
219
+ "loss": 1.244,
220
+ "step": 29
221
+ },
222
+ {
223
+ "epoch": 0.06,
224
+ "grad_norm": 2.498039484024048,
225
+ "learning_rate": 0.00019908848681582391,
226
+ "loss": 1.8747,
227
+ "step": 30
228
+ },
229
+ {
230
+ "epoch": 0.07,
231
+ "grad_norm": 0.9571327567100525,
232
+ "learning_rate": 0.0001989952134772769,
233
+ "loss": 1.3877,
234
+ "step": 31
235
+ },
236
+ {
237
+ "epoch": 0.07,
238
+ "grad_norm": 2.0039713382720947,
239
+ "learning_rate": 0.00019889742151286247,
240
+ "loss": 2.0081,
241
+ "step": 32
242
+ },
243
+ {
244
+ "epoch": 0.07,
245
+ "grad_norm": 1.1989943981170654,
246
+ "learning_rate": 0.00019879511538628428,
247
+ "loss": 1.4427,
248
+ "step": 33
249
+ },
250
+ {
251
+ "epoch": 0.07,
252
+ "grad_norm": 0.8076533675193787,
253
+ "learning_rate": 0.00019868829976729443,
254
+ "loss": 1.3122,
255
+ "step": 34
256
+ },
257
+ {
258
+ "epoch": 0.07,
259
+ "grad_norm": 3.5690324306488037,
260
+ "learning_rate": 0.00019857697953148037,
261
+ "loss": 1.5759,
262
+ "step": 35
263
+ },
264
+ {
265
+ "epoch": 0.08,
266
+ "grad_norm": 0.7935991883277893,
267
+ "learning_rate": 0.00019846115976004234,
268
+ "loss": 1.2685,
269
+ "step": 36
270
+ },
271
+ {
272
+ "epoch": 0.08,
273
+ "grad_norm": 1.0418881177902222,
274
+ "learning_rate": 0.00019834084573956128,
275
+ "loss": 1.8058,
276
+ "step": 37
277
+ },
278
+ {
279
+ "epoch": 0.08,
280
+ "grad_norm": 1.13619065284729,
281
+ "learning_rate": 0.00019821604296175774,
282
+ "loss": 1.55,
283
+ "step": 38
284
+ },
285
+ {
286
+ "epoch": 0.08,
287
+ "grad_norm": 1.460271954536438,
288
+ "learning_rate": 0.00019808675712324107,
289
+ "loss": 1.3906,
290
+ "step": 39
291
+ },
292
+ {
293
+ "epoch": 0.08,
294
+ "grad_norm": 0.8569309711456299,
295
+ "learning_rate": 0.00019795299412524945,
296
+ "loss": 1.3688,
297
+ "step": 40
298
+ },
299
+ {
300
+ "epoch": 0.09,
301
+ "grad_norm": 1.2582310438156128,
302
+ "learning_rate": 0.00019781476007338058,
303
+ "loss": 1.093,
304
+ "step": 41
305
+ },
306
+ {
307
+ "epoch": 0.09,
308
+ "grad_norm": 0.4148155450820923,
309
+ "learning_rate": 0.00019767206127731281,
310
+ "loss": 1.3204,
311
+ "step": 42
312
+ },
313
+ {
314
+ "epoch": 0.09,
315
+ "grad_norm": 1.2747466564178467,
316
+ "learning_rate": 0.00019752490425051743,
317
+ "loss": 1.0998,
318
+ "step": 43
319
+ },
320
+ {
321
+ "epoch": 0.09,
322
+ "grad_norm": 0.7309204339981079,
323
+ "learning_rate": 0.000197373295709961,
324
+ "loss": 1.6907,
325
+ "step": 44
326
+ },
327
+ {
328
+ "epoch": 0.09,
329
+ "grad_norm": 0.5022898316383362,
330
+ "learning_rate": 0.00019721724257579907,
331
+ "loss": 1.4717,
332
+ "step": 45
333
+ },
334
+ {
335
+ "epoch": 0.1,
336
+ "grad_norm": 0.9706376194953918,
337
+ "learning_rate": 0.00019705675197106016,
338
+ "loss": 1.8908,
339
+ "step": 46
340
+ },
341
+ {
342
+ "epoch": 0.1,
343
+ "grad_norm": 0.6191427111625671,
344
+ "learning_rate": 0.00019689183122132068,
345
+ "loss": 1.3458,
346
+ "step": 47
347
+ },
348
+ {
349
+ "epoch": 0.1,
350
+ "grad_norm": 0.8788885474205017,
351
+ "learning_rate": 0.0001967224878543705,
352
+ "loss": 1.772,
353
+ "step": 48
354
+ },
355
+ {
356
+ "epoch": 0.1,
357
+ "grad_norm": 1.3387707471847534,
358
+ "learning_rate": 0.00019654872959986937,
359
+ "loss": 1.4979,
360
+ "step": 49
361
+ },
362
+ {
363
+ "epoch": 0.11,
364
+ "grad_norm": 1.0316563844680786,
365
+ "learning_rate": 0.0001963705643889941,
366
+ "loss": 1.2347,
367
+ "step": 50
368
+ },
369
+ {
370
+ "epoch": 0.11,
371
+ "grad_norm": 2.2246055603027344,
372
+ "learning_rate": 0.00019618800035407658,
373
+ "loss": 1.7885,
374
+ "step": 51
375
+ },
376
+ {
377
+ "epoch": 0.11,
378
+ "grad_norm": 1.443323016166687,
379
+ "learning_rate": 0.0001960010458282326,
380
+ "loss": 1.2274,
381
+ "step": 52
382
+ },
383
+ {
384
+ "epoch": 0.11,
385
+ "grad_norm": 0.8868201375007629,
386
+ "learning_rate": 0.0001958097093449813,
387
+ "loss": 0.9314,
388
+ "step": 53
389
+ },
390
+ {
391
+ "epoch": 0.11,
392
+ "grad_norm": 2.7264301776885986,
393
+ "learning_rate": 0.00019561399963785586,
394
+ "loss": 1.1364,
395
+ "step": 54
396
+ },
397
+ {
398
+ "epoch": 0.12,
399
+ "grad_norm": 1.450035810470581,
400
+ "learning_rate": 0.00019541392564000488,
401
+ "loss": 1.6993,
402
+ "step": 55
403
+ },
404
+ {
405
+ "epoch": 0.12,
406
+ "grad_norm": 1.0921446084976196,
407
+ "learning_rate": 0.00019520949648378443,
408
+ "loss": 1.4098,
409
+ "step": 56
410
+ },
411
+ {
412
+ "epoch": 0.12,
413
+ "grad_norm": 0.580201268196106,
414
+ "learning_rate": 0.00019500072150034137,
415
+ "loss": 1.0974,
416
+ "step": 57
417
+ },
418
+ {
419
+ "epoch": 0.12,
420
+ "grad_norm": 1.6637622117996216,
421
+ "learning_rate": 0.00019478761021918728,
422
+ "loss": 1.4646,
423
+ "step": 58
424
+ },
425
+ {
426
+ "epoch": 0.12,
427
+ "grad_norm": 0.7193565964698792,
428
+ "learning_rate": 0.00019457017236776373,
429
+ "loss": 1.2315,
430
+ "step": 59
431
+ },
432
+ {
433
+ "epoch": 0.13,
434
+ "grad_norm": 0.8072863817214966,
435
+ "learning_rate": 0.00019434841787099803,
436
+ "loss": 1.1918,
437
+ "step": 60
438
+ },
439
+ {
440
+ "epoch": 0.13,
441
+ "grad_norm": 1.3189361095428467,
442
+ "learning_rate": 0.00019412235685085035,
443
+ "loss": 1.5442,
444
+ "step": 61
445
+ },
446
+ {
447
+ "epoch": 0.13,
448
+ "grad_norm": 1.0731955766677856,
449
+ "learning_rate": 0.00019389199962585157,
450
+ "loss": 0.9577,
451
+ "step": 62
452
+ },
453
+ {
454
+ "epoch": 0.13,
455
+ "grad_norm": 0.7714097499847412,
456
+ "learning_rate": 0.0001936573567106325,
457
+ "loss": 1.6435,
458
+ "step": 63
459
+ },
460
+ {
461
+ "epoch": 0.13,
462
+ "grad_norm": 1.1686166524887085,
463
+ "learning_rate": 0.00019341843881544372,
464
+ "loss": 1.7296,
465
+ "step": 64
466
+ },
467
+ {
468
+ "epoch": 0.14,
469
+ "grad_norm": 0.8492275476455688,
470
+ "learning_rate": 0.00019317525684566685,
471
+ "loss": 1.4221,
472
+ "step": 65
473
+ },
474
+ {
475
+ "epoch": 0.14,
476
+ "grad_norm": 0.8079515099525452,
477
+ "learning_rate": 0.00019292782190131677,
478
+ "loss": 1.234,
479
+ "step": 66
480
+ },
481
+ {
482
+ "epoch": 0.14,
483
+ "grad_norm": 0.6675179600715637,
484
+ "learning_rate": 0.00019267614527653488,
485
+ "loss": 1.2457,
486
+ "step": 67
487
+ },
488
+ {
489
+ "epoch": 0.14,
490
+ "grad_norm": 0.5377606153488159,
491
+ "learning_rate": 0.0001924202384590736,
492
+ "loss": 1.4115,
493
+ "step": 68
494
+ },
495
+ {
496
+ "epoch": 0.15,
497
+ "grad_norm": 0.6757211089134216,
498
+ "learning_rate": 0.0001921601131297721,
499
+ "loss": 1.0735,
500
+ "step": 69
501
+ },
502
+ {
503
+ "epoch": 0.15,
504
+ "grad_norm": 0.585841178894043,
505
+ "learning_rate": 0.00019189578116202307,
506
+ "loss": 1.3859,
507
+ "step": 70
508
+ },
509
+ {
510
+ "epoch": 0.15,
511
+ "grad_norm": 0.6633312106132507,
512
+ "learning_rate": 0.00019162725462123072,
513
+ "loss": 1.1772,
514
+ "step": 71
515
+ },
516
+ {
517
+ "epoch": 0.15,
518
+ "grad_norm": 0.7894064784049988,
519
+ "learning_rate": 0.0001913545457642601,
520
+ "loss": 0.9443,
521
+ "step": 72
522
+ },
523
+ {
524
+ "epoch": 0.15,
525
+ "grad_norm": 0.7125688195228577,
526
+ "learning_rate": 0.00019107766703887764,
527
+ "loss": 1.2188,
528
+ "step": 73
529
+ },
530
+ {
531
+ "epoch": 0.16,
532
+ "grad_norm": 0.4715336561203003,
533
+ "learning_rate": 0.00019079663108318302,
534
+ "loss": 1.3095,
535
+ "step": 74
536
+ },
537
+ {
538
+ "epoch": 0.16,
539
+ "grad_norm": 3.017150402069092,
540
+ "learning_rate": 0.00019051145072503215,
541
+ "loss": 1.704,
542
+ "step": 75
543
+ },
544
+ {
545
+ "epoch": 0.16,
546
+ "grad_norm": 0.5130548477172852,
547
+ "learning_rate": 0.00019022213898145176,
548
+ "loss": 1.2175,
549
+ "step": 76
550
+ },
551
+ {
552
+ "epoch": 0.16,
553
+ "grad_norm": 0.931109607219696,
554
+ "learning_rate": 0.00018992870905804534,
555
+ "loss": 0.9057,
556
+ "step": 77
557
+ },
558
+ {
559
+ "epoch": 0.16,
560
+ "grad_norm": 3.687540292739868,
561
+ "learning_rate": 0.0001896311743483901,
562
+ "loss": 1.0161,
563
+ "step": 78
564
+ },
565
+ {
566
+ "epoch": 0.17,
567
+ "grad_norm": 0.5885124802589417,
568
+ "learning_rate": 0.00018932954843342591,
569
+ "loss": 1.2787,
570
+ "step": 79
571
+ },
572
+ {
573
+ "epoch": 0.17,
574
+ "grad_norm": 0.636814534664154,
575
+ "learning_rate": 0.00018902384508083517,
576
+ "loss": 1.0253,
577
+ "step": 80
578
+ },
579
+ {
580
+ "epoch": 0.17,
581
+ "grad_norm": 1.0739303827285767,
582
+ "learning_rate": 0.0001887140782444145,
583
+ "loss": 1.1437,
584
+ "step": 81
585
+ },
586
+ {
587
+ "epoch": 0.17,
588
+ "grad_norm": 0.6316006183624268,
589
+ "learning_rate": 0.00018840026206343784,
590
+ "loss": 0.4953,
591
+ "step": 82
592
+ },
593
+ {
594
+ "epoch": 0.17,
595
+ "grad_norm": 1.1502597332000732,
596
+ "learning_rate": 0.00018808241086201103,
597
+ "loss": 1.043,
598
+ "step": 83
599
+ },
600
+ {
601
+ "epoch": 0.18,
602
+ "grad_norm": 1.3769752979278564,
603
+ "learning_rate": 0.0001877605391484179,
604
+ "loss": 1.2975,
605
+ "step": 84
606
+ },
607
+ {
608
+ "epoch": 0.18,
609
+ "grad_norm": 0.9198704957962036,
610
+ "learning_rate": 0.00018743466161445823,
611
+ "loss": 1.3415,
612
+ "step": 85
613
+ },
614
+ {
615
+ "epoch": 0.18,
616
+ "grad_norm": 0.8441985845565796,
617
+ "learning_rate": 0.00018710479313477696,
618
+ "loss": 0.9262,
619
+ "step": 86
620
+ },
621
+ {
622
+ "epoch": 0.18,
623
+ "grad_norm": 0.6904205679893494,
624
+ "learning_rate": 0.00018677094876618538,
625
+ "loss": 1.0266,
626
+ "step": 87
627
+ },
628
+ {
629
+ "epoch": 0.19,
630
+ "grad_norm": 0.9781098365783691,
631
+ "learning_rate": 0.00018643314374697378,
632
+ "loss": 1.8946,
633
+ "step": 88
634
+ },
635
+ {
636
+ "epoch": 0.19,
637
+ "grad_norm": 0.5499415397644043,
638
+ "learning_rate": 0.00018609139349621588,
639
+ "loss": 0.8428,
640
+ "step": 89
641
+ },
642
+ {
643
+ "epoch": 0.19,
644
+ "grad_norm": 1.4500677585601807,
645
+ "learning_rate": 0.0001857457136130651,
646
+ "loss": 1.3847,
647
+ "step": 90
648
+ },
649
+ {
650
+ "epoch": 0.19,
651
+ "grad_norm": 1.2159172296524048,
652
+ "learning_rate": 0.00018539611987604258,
653
+ "loss": 1.0733,
654
+ "step": 91
655
+ },
656
+ {
657
+ "epoch": 0.19,
658
+ "grad_norm": 0.3588328957557678,
659
+ "learning_rate": 0.00018504262824231674,
660
+ "loss": 1.3488,
661
+ "step": 92
662
+ },
663
+ {
664
+ "epoch": 0.2,
665
+ "grad_norm": 0.6259031891822815,
666
+ "learning_rate": 0.00018468525484697525,
667
+ "loss": 1.9598,
668
+ "step": 93
669
+ },
670
+ {
671
+ "epoch": 0.2,
672
+ "grad_norm": 1.32454252243042,
673
+ "learning_rate": 0.00018432401600228823,
674
+ "loss": 0.7533,
675
+ "step": 94
676
+ },
677
+ {
678
+ "epoch": 0.2,
679
+ "grad_norm": 0.4529890716075897,
680
+ "learning_rate": 0.00018395892819696389,
681
+ "loss": 1.816,
682
+ "step": 95
683
+ },
684
+ {
685
+ "epoch": 0.2,
686
+ "grad_norm": 0.5825135707855225,
687
+ "learning_rate": 0.00018359000809539585,
688
+ "loss": 1.104,
689
+ "step": 96
690
+ },
691
+ {
692
+ "epoch": 0.2,
693
+ "grad_norm": 1.4329938888549805,
694
+ "learning_rate": 0.0001832172725369024,
695
+ "loss": 1.37,
696
+ "step": 97
697
+ },
698
+ {
699
+ "epoch": 0.21,
700
+ "grad_norm": 1.0493029356002808,
701
+ "learning_rate": 0.00018284073853495807,
702
+ "loss": 1.3342,
703
+ "step": 98
704
+ },
705
+ {
706
+ "epoch": 0.21,
707
+ "grad_norm": 0.8605116605758667,
708
+ "learning_rate": 0.00018246042327641678,
709
+ "loss": 1.26,
710
+ "step": 99
711
+ },
712
+ {
713
+ "epoch": 0.21,
714
+ "grad_norm": 0.775687575340271,
715
+ "learning_rate": 0.00018207634412072764,
716
+ "loss": 0.8628,
717
+ "step": 100
718
+ },
719
+ {
720
+ "epoch": 0.21,
721
+ "grad_norm": 4.881119251251221,
722
+ "learning_rate": 0.0001816885185991424,
723
+ "loss": 1.6938,
724
+ "step": 101
725
+ },
726
+ {
727
+ "epoch": 0.21,
728
+ "grad_norm": 1.4081553220748901,
729
+ "learning_rate": 0.00018129696441391522,
730
+ "loss": 1.7014,
731
+ "step": 102
732
+ },
733
+ {
734
+ "epoch": 0.22,
735
+ "grad_norm": 0.636123538017273,
736
+ "learning_rate": 0.00018090169943749476,
737
+ "loss": 1.4061,
738
+ "step": 103
739
+ },
740
+ {
741
+ "epoch": 0.22,
742
+ "grad_norm": 0.2846980392932892,
743
+ "learning_rate": 0.00018050274171170836,
744
+ "loss": 0.5465,
745
+ "step": 104
746
+ },
747
+ {
748
+ "epoch": 0.22,
749
+ "grad_norm": 1.0350561141967773,
750
+ "learning_rate": 0.00018010010944693848,
751
+ "loss": 1.7158,
752
+ "step": 105
753
+ },
754
+ {
755
+ "epoch": 0.22,
756
+ "grad_norm": 1.09168541431427,
757
+ "learning_rate": 0.0001796938210212915,
758
+ "loss": 1.0047,
759
+ "step": 106
760
+ },
761
+ {
762
+ "epoch": 0.23,
763
+ "grad_norm": 0.8954039812088013,
764
+ "learning_rate": 0.00017928389497975895,
765
+ "loss": 1.7889,
766
+ "step": 107
767
+ },
768
+ {
769
+ "epoch": 0.23,
770
+ "grad_norm": 0.9749327301979065,
771
+ "learning_rate": 0.00017887035003337083,
772
+ "loss": 1.9958,
773
+ "step": 108
774
+ },
775
+ {
776
+ "epoch": 0.23,
777
+ "grad_norm": 1.0174291133880615,
778
+ "learning_rate": 0.00017845320505834175,
779
+ "loss": 1.5635,
780
+ "step": 109
781
+ },
782
+ {
783
+ "epoch": 0.23,
784
+ "grad_norm": 1.013778805732727,
785
+ "learning_rate": 0.0001780324790952092,
786
+ "loss": 1.1228,
787
+ "step": 110
788
+ },
789
+ {
790
+ "epoch": 0.23,
791
+ "grad_norm": 0.6990927457809448,
792
+ "learning_rate": 0.0001776081913479645,
793
+ "loss": 1.2748,
794
+ "step": 111
795
+ },
796
+ {
797
+ "epoch": 0.24,
798
+ "grad_norm": 1.4960625171661377,
799
+ "learning_rate": 0.0001771803611831762,
800
+ "loss": 1.1509,
801
+ "step": 112
802
+ },
803
+ {
804
+ "epoch": 0.24,
805
+ "grad_norm": 0.7278648018836975,
806
+ "learning_rate": 0.0001767490081291062,
807
+ "loss": 1.1221,
808
+ "step": 113
809
+ },
810
+ {
811
+ "epoch": 0.24,
812
+ "grad_norm": 0.7677181363105774,
813
+ "learning_rate": 0.0001763141518748182,
814
+ "loss": 1.7333,
815
+ "step": 114
816
+ },
817
+ {
818
+ "epoch": 0.24,
819
+ "grad_norm": 1.0699597597122192,
820
+ "learning_rate": 0.0001758758122692791,
821
+ "loss": 1.3511,
822
+ "step": 115
823
+ },
824
+ {
825
+ "epoch": 0.24,
826
+ "grad_norm": 0.5539786219596863,
827
+ "learning_rate": 0.00017543400932045307,
828
+ "loss": 1.171,
829
+ "step": 116
830
+ },
831
+ {
832
+ "epoch": 0.25,
833
+ "grad_norm": 0.4356689751148224,
834
+ "learning_rate": 0.0001749887631943882,
835
+ "loss": 1.2168,
836
+ "step": 117
837
+ },
838
+ {
839
+ "epoch": 0.25,
840
+ "grad_norm": 0.6579217910766602,
841
+ "learning_rate": 0.00017454009421429597,
842
+ "loss": 1.331,
843
+ "step": 118
844
+ },
845
+ {
846
+ "epoch": 0.25,
847
+ "grad_norm": 2.777512311935425,
848
+ "learning_rate": 0.00017408802285962368,
849
+ "loss": 1.4826,
850
+ "step": 119
851
+ },
852
+ {
853
+ "epoch": 0.25,
854
+ "eval_loss": 1.2498269081115723,
855
+ "eval_runtime": 11.2195,
856
+ "eval_samples_per_second": 8.913,
857
+ "eval_steps_per_second": 8.913,
858
+ "step": 119
859
+ },
860
+ {
861
+ "epoch": 0.25,
862
+ "grad_norm": 0.47785863280296326,
863
+ "learning_rate": 0.00017363256976511972,
864
+ "loss": 1.4644,
865
+ "step": 120
866
+ },
867
+ {
868
+ "epoch": 0.25,
869
+ "grad_norm": 0.5930947661399841,
870
+ "learning_rate": 0.00017317375571989158,
871
+ "loss": 1.591,
872
+ "step": 121
873
+ },
874
+ {
875
+ "epoch": 0.26,
876
+ "grad_norm": 0.7645952701568604,
877
+ "learning_rate": 0.00017271160166645695,
878
+ "loss": 1.2038,
879
+ "step": 122
880
+ },
881
+ {
882
+ "epoch": 0.26,
883
+ "grad_norm": 0.7254743576049805,
884
+ "learning_rate": 0.0001722461286997879,
885
+ "loss": 1.1559,
886
+ "step": 123
887
+ },
888
+ {
889
+ "epoch": 0.26,
890
+ "grad_norm": 0.39301592111587524,
891
+ "learning_rate": 0.00017177735806634789,
892
+ "loss": 1.1492,
893
+ "step": 124
894
+ },
895
+ {
896
+ "epoch": 0.26,
897
+ "grad_norm": 0.8771683573722839,
898
+ "learning_rate": 0.00017130531116312203,
899
+ "loss": 1.0438,
900
+ "step": 125
901
+ },
902
+ {
903
+ "epoch": 0.27,
904
+ "grad_norm": 0.6636186242103577,
905
+ "learning_rate": 0.0001708300095366405,
906
+ "loss": 1.0158,
907
+ "step": 126
908
+ },
909
+ {
910
+ "epoch": 0.27,
911
+ "grad_norm": 0.7356956601142883,
912
+ "learning_rate": 0.00017035147488199482,
913
+ "loss": 1.2417,
914
+ "step": 127
915
+ },
916
+ {
917
+ "epoch": 0.27,
918
+ "grad_norm": 3.8965201377868652,
919
+ "learning_rate": 0.00016986972904184784,
920
+ "loss": 1.3653,
921
+ "step": 128
922
+ },
923
+ {
924
+ "epoch": 0.27,
925
+ "grad_norm": 0.6314372420310974,
926
+ "learning_rate": 0.00016938479400543658,
927
+ "loss": 0.9501,
928
+ "step": 129
929
+ },
930
+ {
931
+ "epoch": 0.27,
932
+ "grad_norm": 1.1143038272857666,
933
+ "learning_rate": 0.00016889669190756868,
934
+ "loss": 1.2585,
935
+ "step": 130
936
+ },
937
+ {
938
+ "epoch": 0.28,
939
+ "grad_norm": 0.9126316905021667,
940
+ "learning_rate": 0.00016840544502761176,
941
+ "loss": 0.9933,
942
+ "step": 131
943
+ },
944
+ {
945
+ "epoch": 0.28,
946
+ "grad_norm": 0.7595810294151306,
947
+ "learning_rate": 0.0001679110757884769,
948
+ "loss": 1.3224,
949
+ "step": 132
950
+ },
951
+ {
952
+ "epoch": 0.28,
953
+ "grad_norm": 0.7331580519676208,
954
+ "learning_rate": 0.00016741360675559473,
955
+ "loss": 1.451,
956
+ "step": 133
957
+ },
958
+ {
959
+ "epoch": 0.28,
960
+ "grad_norm": 0.37914204597473145,
961
+ "learning_rate": 0.00016691306063588583,
962
+ "loss": 1.0334,
963
+ "step": 134
964
+ },
965
+ {
966
+ "epoch": 0.28,
967
+ "grad_norm": 0.7935598492622375,
968
+ "learning_rate": 0.00016640946027672392,
969
+ "loss": 1.401,
970
+ "step": 135
971
+ },
972
+ {
973
+ "epoch": 0.29,
974
+ "grad_norm": 0.3880078196525574,
975
+ "learning_rate": 0.00016590282866489319,
976
+ "loss": 1.2831,
977
+ "step": 136
978
+ },
979
+ {
980
+ "epoch": 0.29,
981
+ "grad_norm": 0.7817143201828003,
982
+ "learning_rate": 0.0001653931889255391,
983
+ "loss": 1.2609,
984
+ "step": 137
985
+ },
986
+ {
987
+ "epoch": 0.29,
988
+ "grad_norm": 0.7870498299598694,
989
+ "learning_rate": 0.0001648805643211127,
990
+ "loss": 0.8674,
991
+ "step": 138
992
+ },
993
+ {
994
+ "epoch": 0.29,
995
+ "grad_norm": 0.5795213580131531,
996
+ "learning_rate": 0.00016436497825030884,
997
+ "loss": 0.9604,
998
+ "step": 139
999
+ },
1000
+ {
1001
+ "epoch": 0.29,
1002
+ "grad_norm": 0.5516975522041321,
1003
+ "learning_rate": 0.00016384645424699835,
1004
+ "loss": 0.6344,
1005
+ "step": 140
1006
+ },
1007
+ {
1008
+ "epoch": 0.3,
1009
+ "grad_norm": 1.6294902563095093,
1010
+ "learning_rate": 0.00016332501597915352,
1011
+ "loss": 1.0385,
1012
+ "step": 141
1013
+ },
1014
+ {
1015
+ "epoch": 0.3,
1016
+ "grad_norm": 0.3721281886100769,
1017
+ "learning_rate": 0.00016280068724776797,
1018
+ "loss": 1.0667,
1019
+ "step": 142
1020
+ },
1021
+ {
1022
+ "epoch": 0.3,
1023
+ "grad_norm": 0.632927656173706,
1024
+ "learning_rate": 0.0001622734919857702,
1025
+ "loss": 0.5996,
1026
+ "step": 143
1027
+ },
1028
+ {
1029
+ "epoch": 0.3,
1030
+ "grad_norm": 0.7089216709136963,
1031
+ "learning_rate": 0.0001617434542569313,
1032
+ "loss": 1.0407,
1033
+ "step": 144
1034
+ },
1035
+ {
1036
+ "epoch": 0.31,
1037
+ "grad_norm": 1.2346296310424805,
1038
+ "learning_rate": 0.0001612105982547663,
1039
+ "loss": 1.4111,
1040
+ "step": 145
1041
+ },
1042
+ {
1043
+ "epoch": 0.31,
1044
+ "grad_norm": 0.5850281119346619,
1045
+ "learning_rate": 0.00016067494830143014,
1046
+ "loss": 1.1949,
1047
+ "step": 146
1048
+ },
1049
+ {
1050
+ "epoch": 0.31,
1051
+ "grad_norm": 0.6999644041061401,
1052
+ "learning_rate": 0.00016013652884660723,
1053
+ "loss": 1.2583,
1054
+ "step": 147
1055
+ },
1056
+ {
1057
+ "epoch": 0.31,
1058
+ "grad_norm": 0.6640311479568481,
1059
+ "learning_rate": 0.0001595953644663957,
1060
+ "loss": 0.8627,
1061
+ "step": 148
1062
+ },
1063
+ {
1064
+ "epoch": 0.31,
1065
+ "grad_norm": 1.467826008796692,
1066
+ "learning_rate": 0.00015905147986218547,
1067
+ "loss": 1.4436,
1068
+ "step": 149
1069
+ },
1070
+ {
1071
+ "epoch": 0.32,
1072
+ "grad_norm": 0.5436001420021057,
1073
+ "learning_rate": 0.00015850489985953076,
1074
+ "loss": 1.1029,
1075
+ "step": 150
1076
+ },
1077
+ {
1078
+ "epoch": 0.32,
1079
+ "grad_norm": 1.3373098373413086,
1080
+ "learning_rate": 0.000157955649407017,
1081
+ "loss": 1.0907,
1082
+ "step": 151
1083
+ },
1084
+ {
1085
+ "epoch": 0.32,
1086
+ "grad_norm": 0.8601608276367188,
1087
+ "learning_rate": 0.00015740375357512195,
1088
+ "loss": 1.285,
1089
+ "step": 152
1090
+ },
1091
+ {
1092
+ "epoch": 0.32,
1093
+ "grad_norm": 1.090238332748413,
1094
+ "learning_rate": 0.0001568492375550715,
1095
+ "loss": 1.1262,
1096
+ "step": 153
1097
+ },
1098
+ {
1099
+ "epoch": 0.32,
1100
+ "grad_norm": 1.0742828845977783,
1101
+ "learning_rate": 0.00015629212665768978,
1102
+ "loss": 0.9301,
1103
+ "step": 154
1104
+ },
1105
+ {
1106
+ "epoch": 0.33,
1107
+ "grad_norm": 0.6687757968902588,
1108
+ "learning_rate": 0.00015573244631224365,
1109
+ "loss": 1.3763,
1110
+ "step": 155
1111
+ },
1112
+ {
1113
+ "epoch": 0.33,
1114
+ "grad_norm": 0.322456032037735,
1115
+ "learning_rate": 0.00015517022206528233,
1116
+ "loss": 1.157,
1117
+ "step": 156
1118
+ },
1119
+ {
1120
+ "epoch": 0.33,
1121
+ "grad_norm": 1.552617073059082,
1122
+ "learning_rate": 0.00015460547957947104,
1123
+ "loss": 1.5864,
1124
+ "step": 157
1125
+ },
1126
+ {
1127
+ "epoch": 0.33,
1128
+ "grad_norm": 1.0862557888031006,
1129
+ "learning_rate": 0.0001540382446324198,
1130
+ "loss": 1.2378,
1131
+ "step": 158
1132
+ },
1133
+ {
1134
+ "epoch": 0.33,
1135
+ "grad_norm": 0.6755203008651733,
1136
+ "learning_rate": 0.00015346854311550673,
1137
+ "loss": 1.1782,
1138
+ "step": 159
1139
+ },
1140
+ {
1141
+ "epoch": 0.34,
1142
+ "grad_norm": 0.5506089329719543,
1143
+ "learning_rate": 0.00015289640103269625,
1144
+ "loss": 1.5313,
1145
+ "step": 160
1146
+ },
1147
+ {
1148
+ "epoch": 0.34,
1149
+ "grad_norm": 0.5224264860153198,
1150
+ "learning_rate": 0.0001523218444993522,
1151
+ "loss": 1.1505,
1152
+ "step": 161
1153
+ },
1154
+ {
1155
+ "epoch": 0.34,
1156
+ "grad_norm": 0.8278419971466064,
1157
+ "learning_rate": 0.00015174489974104574,
1158
+ "loss": 1.4319,
1159
+ "step": 162
1160
+ },
1161
+ {
1162
+ "epoch": 0.34,
1163
+ "grad_norm": 0.9323415160179138,
1164
+ "learning_rate": 0.00015116559309235825,
1165
+ "loss": 1.3218,
1166
+ "step": 163
1167
+ },
1168
+ {
1169
+ "epoch": 0.35,
1170
+ "grad_norm": 1.1334632635116577,
1171
+ "learning_rate": 0.00015058395099567935,
1172
+ "loss": 1.0519,
1173
+ "step": 164
1174
+ },
1175
+ {
1176
+ "epoch": 0.35,
1177
+ "grad_norm": 0.3949350118637085,
1178
+ "learning_rate": 0.00015000000000000001,
1179
+ "loss": 1.0169,
1180
+ "step": 165
1181
+ },
1182
+ {
1183
+ "epoch": 0.35,
1184
+ "grad_norm": 0.9846246242523193,
1185
+ "learning_rate": 0.0001494137667597006,
1186
+ "loss": 1.8383,
1187
+ "step": 166
1188
+ },
1189
+ {
1190
+ "epoch": 0.35,
1191
+ "grad_norm": 0.7132427096366882,
1192
+ "learning_rate": 0.0001488252780333342,
1193
+ "loss": 1.1292,
1194
+ "step": 167
1195
+ },
1196
+ {
1197
+ "epoch": 0.35,
1198
+ "grad_norm": 1.259857177734375,
1199
+ "learning_rate": 0.00014823456068240558,
1200
+ "loss": 0.929,
1201
+ "step": 168
1202
+ },
1203
+ {
1204
+ "epoch": 0.36,
1205
+ "grad_norm": 1.3703701496124268,
1206
+ "learning_rate": 0.00014764164167014451,
1207
+ "loss": 1.5655,
1208
+ "step": 169
1209
+ },
1210
+ {
1211
+ "epoch": 0.36,
1212
+ "grad_norm": 0.5980277061462402,
1213
+ "learning_rate": 0.0001470465480602756,
1214
+ "loss": 1.1459,
1215
+ "step": 170
1216
+ },
1217
+ {
1218
+ "epoch": 0.36,
1219
+ "grad_norm": 1.2204481363296509,
1220
+ "learning_rate": 0.00014644930701578253,
1221
+ "loss": 0.8177,
1222
+ "step": 171
1223
+ },
1224
+ {
1225
+ "epoch": 0.36,
1226
+ "grad_norm": 0.325509637594223,
1227
+ "learning_rate": 0.00014584994579766865,
1228
+ "loss": 1.2372,
1229
+ "step": 172
1230
+ },
1231
+ {
1232
+ "epoch": 0.36,
1233
+ "grad_norm": 1.206936001777649,
1234
+ "learning_rate": 0.0001452484917637122,
1235
+ "loss": 1.3148,
1236
+ "step": 173
1237
+ },
1238
+ {
1239
+ "epoch": 0.37,
1240
+ "grad_norm": 1.0160785913467407,
1241
+ "learning_rate": 0.00014464497236721778,
1242
+ "loss": 1.1832,
1243
+ "step": 174
1244
+ },
1245
+ {
1246
+ "epoch": 0.37,
1247
+ "grad_norm": 1.3579516410827637,
1248
+ "learning_rate": 0.00014403941515576344,
1249
+ "loss": 1.3798,
1250
+ "step": 175
1251
+ },
1252
+ {
1253
+ "epoch": 0.37,
1254
+ "grad_norm": 0.47968143224716187,
1255
+ "learning_rate": 0.00014343184776994289,
1256
+ "loss": 1.0797,
1257
+ "step": 176
1258
+ },
1259
+ {
1260
+ "epoch": 0.37,
1261
+ "grad_norm": 0.9022389650344849,
1262
+ "learning_rate": 0.00014282229794210404,
1263
+ "loss": 1.3824,
1264
+ "step": 177
1265
+ },
1266
+ {
1267
+ "epoch": 0.37,
1268
+ "grad_norm": 0.9592376947402954,
1269
+ "learning_rate": 0.0001422107934950832,
1270
+ "loss": 0.7374,
1271
+ "step": 178
1272
+ },
1273
+ {
1274
+ "epoch": 0.38,
1275
+ "grad_norm": 0.8611739873886108,
1276
+ "learning_rate": 0.0001415973623409351,
1277
+ "loss": 1.4377,
1278
+ "step": 179
1279
+ },
1280
+ {
1281
+ "epoch": 0.38,
1282
+ "grad_norm": 0.4279676079750061,
1283
+ "learning_rate": 0.00014098203247965875,
1284
+ "loss": 1.7355,
1285
+ "step": 180
1286
+ },
1287
+ {
1288
+ "epoch": 0.38,
1289
+ "grad_norm": 0.669457733631134,
1290
+ "learning_rate": 0.00014036483199791948,
1291
+ "loss": 1.3662,
1292
+ "step": 181
1293
+ },
1294
+ {
1295
+ "epoch": 0.38,
1296
+ "grad_norm": 0.8061684370040894,
1297
+ "learning_rate": 0.00013974578906776684,
1298
+ "loss": 1.2989,
1299
+ "step": 182
1300
+ },
1301
+ {
1302
+ "epoch": 0.39,
1303
+ "grad_norm": 0.6208318471908569,
1304
+ "learning_rate": 0.00013912493194534874,
1305
+ "loss": 1.4503,
1306
+ "step": 183
1307
+ },
1308
+ {
1309
+ "epoch": 0.39,
1310
+ "grad_norm": 0.9276289343833923,
1311
+ "learning_rate": 0.0001385022889696218,
1312
+ "loss": 1.7339,
1313
+ "step": 184
1314
+ },
1315
+ {
1316
+ "epoch": 0.39,
1317
+ "grad_norm": 0.5193164944648743,
1318
+ "learning_rate": 0.0001378778885610576,
1319
+ "loss": 1.0053,
1320
+ "step": 185
1321
+ },
1322
+ {
1323
+ "epoch": 0.39,
1324
+ "grad_norm": 0.7712852954864502,
1325
+ "learning_rate": 0.00013725175922034565,
1326
+ "loss": 0.7669,
1327
+ "step": 186
1328
+ },
1329
+ {
1330
+ "epoch": 0.39,
1331
+ "grad_norm": 0.6915028691291809,
1332
+ "learning_rate": 0.00013662392952709228,
1333
+ "loss": 1.2908,
1334
+ "step": 187
1335
+ },
1336
+ {
1337
+ "epoch": 0.4,
1338
+ "grad_norm": 0.8135898113250732,
1339
+ "learning_rate": 0.00013599442813851632,
1340
+ "loss": 1.2639,
1341
+ "step": 188
1342
+ },
1343
+ {
1344
+ "epoch": 0.4,
1345
+ "grad_norm": 0.9134801626205444,
1346
+ "learning_rate": 0.00013536328378814093,
1347
+ "loss": 1.3689,
1348
+ "step": 189
1349
+ },
1350
+ {
1351
+ "epoch": 0.4,
1352
+ "grad_norm": 0.3660939037799835,
1353
+ "learning_rate": 0.00013473052528448201,
1354
+ "loss": 1.196,
1355
+ "step": 190
1356
+ },
1357
+ {
1358
+ "epoch": 0.4,
1359
+ "grad_norm": 3.6361420154571533,
1360
+ "learning_rate": 0.00013409618150973348,
1361
+ "loss": 2.6822,
1362
+ "step": 191
1363
+ },
1364
+ {
1365
+ "epoch": 0.4,
1366
+ "grad_norm": 0.4731757938861847,
1367
+ "learning_rate": 0.0001334602814184486,
1368
+ "loss": 1.1966,
1369
+ "step": 192
1370
+ },
1371
+ {
1372
+ "epoch": 0.41,
1373
+ "grad_norm": 0.3311164081096649,
1374
+ "learning_rate": 0.00013282285403621864,
1375
+ "loss": 1.4858,
1376
+ "step": 193
1377
+ },
1378
+ {
1379
+ "epoch": 0.41,
1380
+ "grad_norm": 0.9196639060974121,
1381
+ "learning_rate": 0.00013218392845834787,
1382
+ "loss": 1.2163,
1383
+ "step": 194
1384
+ },
1385
+ {
1386
+ "epoch": 0.41,
1387
+ "grad_norm": 1.2580674886703491,
1388
+ "learning_rate": 0.00013154353384852558,
1389
+ "loss": 1.467,
1390
+ "step": 195
1391
+ },
1392
+ {
1393
+ "epoch": 0.41,
1394
+ "grad_norm": 1.3060836791992188,
1395
+ "learning_rate": 0.00013090169943749476,
1396
+ "loss": 2.2125,
1397
+ "step": 196
1398
+ },
1399
+ {
1400
+ "epoch": 0.41,
1401
+ "grad_norm": 0.5120143294334412,
1402
+ "learning_rate": 0.00013025845452171807,
1403
+ "loss": 1.3174,
1404
+ "step": 197
1405
+ },
1406
+ {
1407
+ "epoch": 0.42,
1408
+ "grad_norm": 0.9528945684432983,
1409
+ "learning_rate": 0.00012961382846204055,
1410
+ "loss": 1.7378,
1411
+ "step": 198
1412
+ },
1413
+ {
1414
+ "epoch": 0.42,
1415
+ "grad_norm": 0.5604123473167419,
1416
+ "learning_rate": 0.00012896785068234926,
1417
+ "loss": 1.287,
1418
+ "step": 199
1419
+ },
1420
+ {
1421
+ "epoch": 0.42,
1422
+ "grad_norm": 0.5821733474731445,
1423
+ "learning_rate": 0.00012832055066823038,
1424
+ "loss": 1.4721,
1425
+ "step": 200
1426
+ },
1427
+ {
1428
+ "epoch": 0.42,
1429
+ "grad_norm": 1.4492989778518677,
1430
+ "learning_rate": 0.0001276719579656236,
1431
+ "loss": 1.2461,
1432
+ "step": 201
1433
+ },
1434
+ {
1435
+ "epoch": 0.43,
1436
+ "grad_norm": 1.423685908317566,
1437
+ "learning_rate": 0.00012702210217947288,
1438
+ "loss": 0.9973,
1439
+ "step": 202
1440
+ },
1441
+ {
1442
+ "epoch": 0.43,
1443
+ "grad_norm": 0.5945116877555847,
1444
+ "learning_rate": 0.0001263710129723757,
1445
+ "loss": 0.6836,
1446
+ "step": 203
1447
+ },
1448
+ {
1449
+ "epoch": 0.43,
1450
+ "grad_norm": 0.8192650079727173,
1451
+ "learning_rate": 0.00012571872006322888,
1452
+ "loss": 1.236,
1453
+ "step": 204
1454
+ },
1455
+ {
1456
+ "epoch": 0.43,
1457
+ "grad_norm": 0.35752618312835693,
1458
+ "learning_rate": 0.00012506525322587207,
1459
+ "loss": 1.2113,
1460
+ "step": 205
1461
+ },
1462
+ {
1463
+ "epoch": 0.43,
1464
+ "grad_norm": 0.5102562308311462,
1465
+ "learning_rate": 0.00012441064228772874,
1466
+ "loss": 0.835,
1467
+ "step": 206
1468
+ },
1469
+ {
1470
+ "epoch": 0.44,
1471
+ "grad_norm": 0.6736109852790833,
1472
+ "learning_rate": 0.0001237549171284447,
1473
+ "loss": 1.389,
1474
+ "step": 207
1475
+ },
1476
+ {
1477
+ "epoch": 0.44,
1478
+ "grad_norm": 0.7494972348213196,
1479
+ "learning_rate": 0.00012309810767852433,
1480
+ "loss": 1.0185,
1481
+ "step": 208
1482
+ },
1483
+ {
1484
+ "epoch": 0.44,
1485
+ "grad_norm": 0.34725117683410645,
1486
+ "learning_rate": 0.0001224402439179643,
1487
+ "loss": 0.9023,
1488
+ "step": 209
1489
+ },
1490
+ {
1491
+ "epoch": 0.44,
1492
+ "grad_norm": 0.5315357446670532,
1493
+ "learning_rate": 0.00012178135587488515,
1494
+ "loss": 0.9621,
1495
+ "step": 210
1496
+ },
1497
+ {
1498
+ "epoch": 0.44,
1499
+ "grad_norm": 0.4834609031677246,
1500
+ "learning_rate": 0.00012112147362416076,
1501
+ "loss": 0.9703,
1502
+ "step": 211
1503
+ },
1504
+ {
1505
+ "epoch": 0.45,
1506
+ "grad_norm": 0.5364122986793518,
1507
+ "learning_rate": 0.0001204606272860454,
1508
+ "loss": 1.4784,
1509
+ "step": 212
1510
+ },
1511
+ {
1512
+ "epoch": 0.45,
1513
+ "grad_norm": 1.008988380432129,
1514
+ "learning_rate": 0.00011979884702479909,
1515
+ "loss": 1.6889,
1516
+ "step": 213
1517
+ },
1518
+ {
1519
+ "epoch": 0.45,
1520
+ "grad_norm": 0.8513673543930054,
1521
+ "learning_rate": 0.00011913616304731063,
1522
+ "loss": 1.4391,
1523
+ "step": 214
1524
+ },
1525
+ {
1526
+ "epoch": 0.45,
1527
+ "grad_norm": 1.0368411540985107,
1528
+ "learning_rate": 0.00011847260560171896,
1529
+ "loss": 1.4572,
1530
+ "step": 215
1531
+ },
1532
+ {
1533
+ "epoch": 0.45,
1534
+ "grad_norm": 0.43699911236763,
1535
+ "learning_rate": 0.00011780820497603215,
1536
+ "loss": 0.9995,
1537
+ "step": 216
1538
+ },
1539
+ {
1540
+ "epoch": 0.46,
1541
+ "grad_norm": 1.1479334831237793,
1542
+ "learning_rate": 0.00011714299149674537,
1543
+ "loss": 0.9971,
1544
+ "step": 217
1545
+ },
1546
+ {
1547
+ "epoch": 0.46,
1548
+ "grad_norm": 0.6493399739265442,
1549
+ "learning_rate": 0.00011647699552745628,
1550
+ "loss": 1.1328,
1551
+ "step": 218
1552
+ },
1553
+ {
1554
+ "epoch": 0.46,
1555
+ "grad_norm": 0.8177739977836609,
1556
+ "learning_rate": 0.00011581024746747924,
1557
+ "loss": 1.2741,
1558
+ "step": 219
1559
+ },
1560
+ {
1561
+ "epoch": 0.46,
1562
+ "grad_norm": 0.31355175375938416,
1563
+ "learning_rate": 0.00011514277775045768,
1564
+ "loss": 1.2813,
1565
+ "step": 220
1566
+ },
1567
+ {
1568
+ "epoch": 0.47,
1569
+ "grad_norm": 0.5200531482696533,
1570
+ "learning_rate": 0.00011447461684297504,
1571
+ "loss": 1.4285,
1572
+ "step": 221
1573
+ },
1574
+ {
1575
+ "epoch": 0.47,
1576
+ "grad_norm": 1.6473718881607056,
1577
+ "learning_rate": 0.00011380579524316406,
1578
+ "loss": 1.5263,
1579
+ "step": 222
1580
+ },
1581
+ {
1582
+ "epoch": 0.47,
1583
+ "grad_norm": 2.004498243331909,
1584
+ "learning_rate": 0.00011313634347931466,
1585
+ "loss": 0.9576,
1586
+ "step": 223
1587
+ },
1588
+ {
1589
+ "epoch": 0.47,
1590
+ "grad_norm": 0.9827050566673279,
1591
+ "learning_rate": 0.00011246629210848061,
1592
+ "loss": 1.3642,
1593
+ "step": 224
1594
+ },
1595
+ {
1596
+ "epoch": 0.47,
1597
+ "grad_norm": 0.6069352626800537,
1598
+ "learning_rate": 0.00011179567171508463,
1599
+ "loss": 1.3768,
1600
+ "step": 225
1601
+ },
1602
+ {
1603
+ "epoch": 0.48,
1604
+ "grad_norm": 0.4674800634384155,
1605
+ "learning_rate": 0.00011112451290952237,
1606
+ "loss": 0.9445,
1607
+ "step": 226
1608
+ },
1609
+ {
1610
+ "epoch": 0.48,
1611
+ "grad_norm": 1.1005616188049316,
1612
+ "learning_rate": 0.00011045284632676536,
1613
+ "loss": 1.5748,
1614
+ "step": 227
1615
+ },
1616
+ {
1617
+ "epoch": 0.48,
1618
+ "grad_norm": 0.578959584236145,
1619
+ "learning_rate": 0.00010978070262496247,
1620
+ "loss": 1.3462,
1621
+ "step": 228
1622
+ },
1623
+ {
1624
+ "epoch": 0.48,
1625
+ "grad_norm": 0.9835721254348755,
1626
+ "learning_rate": 0.00010910811248404065,
1627
+ "loss": 2.2544,
1628
+ "step": 229
1629
+ },
1630
+ {
1631
+ "epoch": 0.48,
1632
+ "grad_norm": 0.37735217809677124,
1633
+ "learning_rate": 0.00010843510660430447,
1634
+ "loss": 1.585,
1635
+ "step": 230
1636
+ },
1637
+ {
1638
+ "epoch": 0.49,
1639
+ "grad_norm": 1.3374781608581543,
1640
+ "learning_rate": 0.00010776171570503499,
1641
+ "loss": 0.7627,
1642
+ "step": 231
1643
+ },
1644
+ {
1645
+ "epoch": 0.49,
1646
+ "grad_norm": 1.3360700607299805,
1647
+ "learning_rate": 0.0001070879705230873,
1648
+ "loss": 1.8169,
1649
+ "step": 232
1650
+ },
1651
+ {
1652
+ "epoch": 0.49,
1653
+ "grad_norm": 0.6257541179656982,
1654
+ "learning_rate": 0.00010641390181148772,
1655
+ "loss": 1.0015,
1656
+ "step": 233
1657
+ },
1658
+ {
1659
+ "epoch": 0.49,
1660
+ "grad_norm": 1.234805703163147,
1661
+ "learning_rate": 0.00010573954033803007,
1662
+ "loss": 1.3024,
1663
+ "step": 234
1664
+ },
1665
+ {
1666
+ "epoch": 0.49,
1667
+ "grad_norm": 2.442201852798462,
1668
+ "learning_rate": 0.00010506491688387127,
1669
+ "loss": 1.3141,
1670
+ "step": 235
1671
+ },
1672
+ {
1673
+ "epoch": 0.5,
1674
+ "grad_norm": 0.39670243859291077,
1675
+ "learning_rate": 0.00010439006224212628,
1676
+ "loss": 0.9339,
1677
+ "step": 236
1678
+ },
1679
+ {
1680
+ "epoch": 0.5,
1681
+ "grad_norm": 0.37090030312538147,
1682
+ "learning_rate": 0.00010371500721646261,
1683
+ "loss": 1.3281,
1684
+ "step": 237
1685
+ },
1686
+ {
1687
+ "epoch": 0.5,
1688
+ "grad_norm": 0.6054628491401672,
1689
+ "learning_rate": 0.0001030397826196943,
1690
+ "loss": 1.2919,
1691
+ "step": 238
1692
+ },
1693
+ {
1694
+ "epoch": 0.5,
1695
+ "eval_loss": 1.2451566457748413,
1696
+ "eval_runtime": 11.2081,
1697
+ "eval_samples_per_second": 8.922,
1698
+ "eval_steps_per_second": 8.922,
1699
+ "step": 238
1700
+ },
1701
+ {
1702
+ "epoch": 0.5,
1703
+ "grad_norm": 0.8905054926872253,
1704
+ "learning_rate": 0.00010236441927237535,
1705
+ "loss": 1.5113,
1706
+ "step": 239
1707
+ },
1708
+ {
1709
+ "epoch": 0.51,
1710
+ "grad_norm": 0.8593491911888123,
1711
+ "learning_rate": 0.0001016889480013931,
1712
+ "loss": 0.9025,
1713
+ "step": 240
1714
+ },
1715
+ {
1716
+ "epoch": 0.51,
1717
+ "grad_norm": 0.9700817465782166,
1718
+ "learning_rate": 0.00010101339963856111,
1719
+ "loss": 1.2504,
1720
+ "step": 241
1721
+ },
1722
+ {
1723
+ "epoch": 0.51,
1724
+ "grad_norm": 1.2512820959091187,
1725
+ "learning_rate": 0.00010033780501921164,
1726
+ "loss": 1.769,
1727
+ "step": 242
1728
+ },
1729
+ {
1730
+ "epoch": 0.51,
1731
+ "grad_norm": 3.91457462310791,
1732
+ "learning_rate": 9.966219498078839e-05,
1733
+ "loss": 2.3025,
1734
+ "step": 243
1735
+ },
1736
+ {
1737
+ "epoch": 0.51,
1738
+ "grad_norm": 2.128582239151001,
1739
+ "learning_rate": 9.898660036143893e-05,
1740
+ "loss": 2.0598,
1741
+ "step": 244
1742
+ },
1743
+ {
1744
+ "epoch": 0.52,
1745
+ "grad_norm": 0.3125651478767395,
1746
+ "learning_rate": 9.83110519986069e-05,
1747
+ "loss": 1.0118,
1748
+ "step": 245
1749
+ },
1750
+ {
1751
+ "epoch": 0.52,
1752
+ "grad_norm": 1.2437289953231812,
1753
+ "learning_rate": 9.763558072762468e-05,
1754
+ "loss": 1.2138,
1755
+ "step": 246
1756
+ },
1757
+ {
1758
+ "epoch": 0.52,
1759
+ "grad_norm": 0.653993546962738,
1760
+ "learning_rate": 9.696021738030575e-05,
1761
+ "loss": 0.983,
1762
+ "step": 247
1763
+ },
1764
+ {
1765
+ "epoch": 0.52,
1766
+ "grad_norm": 1.0555764436721802,
1767
+ "learning_rate": 9.62849927835374e-05,
1768
+ "loss": 1.4967,
1769
+ "step": 248
1770
+ },
1771
+ {
1772
+ "epoch": 0.52,
1773
+ "grad_norm": 0.6005884408950806,
1774
+ "learning_rate": 9.560993775787373e-05,
1775
+ "loss": 0.9319,
1776
+ "step": 249
1777
+ },
1778
+ {
1779
+ "epoch": 0.53,
1780
+ "grad_norm": 0.776595413684845,
1781
+ "learning_rate": 9.493508311612874e-05,
1782
+ "loss": 1.2568,
1783
+ "step": 250
1784
+ },
1785
+ {
1786
+ "epoch": 0.53,
1787
+ "grad_norm": 0.8884586691856384,
1788
+ "learning_rate": 9.426045966196993e-05,
1789
+ "loss": 1.4376,
1790
+ "step": 251
1791
+ },
1792
+ {
1793
+ "epoch": 0.53,
1794
+ "grad_norm": 0.7831926345825195,
1795
+ "learning_rate": 9.358609818851229e-05,
1796
+ "loss": 1.2657,
1797
+ "step": 252
1798
+ },
1799
+ {
1800
+ "epoch": 0.53,
1801
+ "grad_norm": 1.2989636659622192,
1802
+ "learning_rate": 9.291202947691271e-05,
1803
+ "loss": 1.9303,
1804
+ "step": 253
1805
+ },
1806
+ {
1807
+ "epoch": 0.53,
1808
+ "grad_norm": 1.6510024070739746,
1809
+ "learning_rate": 9.223828429496499e-05,
1810
+ "loss": 1.361,
1811
+ "step": 254
1812
+ },
1813
+ {
1814
+ "epoch": 0.54,
1815
+ "grad_norm": 0.6142978668212891,
1816
+ "learning_rate": 9.156489339569554e-05,
1817
+ "loss": 1.2702,
1818
+ "step": 255
1819
+ },
1820
+ {
1821
+ "epoch": 0.54,
1822
+ "grad_norm": 1.1854060888290405,
1823
+ "learning_rate": 9.089188751595936e-05,
1824
+ "loss": 0.6902,
1825
+ "step": 256
1826
+ },
1827
+ {
1828
+ "epoch": 0.54,
1829
+ "grad_norm": 0.6005362868309021,
1830
+ "learning_rate": 9.021929737503757e-05,
1831
+ "loss": 1.0575,
1832
+ "step": 257
1833
+ },
1834
+ {
1835
+ "epoch": 0.54,
1836
+ "grad_norm": 0.7906481027603149,
1837
+ "learning_rate": 8.954715367323468e-05,
1838
+ "loss": 0.9277,
1839
+ "step": 258
1840
+ },
1841
+ {
1842
+ "epoch": 0.55,
1843
+ "grad_norm": 2.450592041015625,
1844
+ "learning_rate": 8.887548709047764e-05,
1845
+ "loss": 1.6923,
1846
+ "step": 259
1847
+ },
1848
+ {
1849
+ "epoch": 0.55,
1850
+ "grad_norm": 0.780250072479248,
1851
+ "learning_rate": 8.820432828491542e-05,
1852
+ "loss": 1.0708,
1853
+ "step": 260
1854
+ },
1855
+ {
1856
+ "epoch": 0.55,
1857
+ "grad_norm": 0.6275424957275391,
1858
+ "learning_rate": 8.753370789151941e-05,
1859
+ "loss": 1.2547,
1860
+ "step": 261
1861
+ },
1862
+ {
1863
+ "epoch": 0.55,
1864
+ "grad_norm": 1.6233257055282593,
1865
+ "learning_rate": 8.686365652068535e-05,
1866
+ "loss": 1.2188,
1867
+ "step": 262
1868
+ },
1869
+ {
1870
+ "epoch": 0.55,
1871
+ "grad_norm": 0.9274204969406128,
1872
+ "learning_rate": 8.619420475683597e-05,
1873
+ "loss": 1.2182,
1874
+ "step": 263
1875
+ },
1876
+ {
1877
+ "epoch": 0.56,
1878
+ "grad_norm": 0.7996556162834167,
1879
+ "learning_rate": 8.552538315702498e-05,
1880
+ "loss": 0.953,
1881
+ "step": 264
1882
+ },
1883
+ {
1884
+ "epoch": 0.56,
1885
+ "grad_norm": 0.8006198406219482,
1886
+ "learning_rate": 8.485722224954237e-05,
1887
+ "loss": 0.8871,
1888
+ "step": 265
1889
+ },
1890
+ {
1891
+ "epoch": 0.56,
1892
+ "grad_norm": 0.3429837226867676,
1893
+ "learning_rate": 8.418975253252078e-05,
1894
+ "loss": 1.3951,
1895
+ "step": 266
1896
+ },
1897
+ {
1898
+ "epoch": 0.56,
1899
+ "grad_norm": 0.6119269728660583,
1900
+ "learning_rate": 8.352300447254372e-05,
1901
+ "loss": 1.4484,
1902
+ "step": 267
1903
+ },
1904
+ {
1905
+ "epoch": 0.56,
1906
+ "grad_norm": 0.8381280303001404,
1907
+ "learning_rate": 8.285700850325467e-05,
1908
+ "loss": 1.4779,
1909
+ "step": 268
1910
+ },
1911
+ {
1912
+ "epoch": 0.57,
1913
+ "grad_norm": 0.9022213816642761,
1914
+ "learning_rate": 8.219179502396787e-05,
1915
+ "loss": 1.6646,
1916
+ "step": 269
1917
+ },
1918
+ {
1919
+ "epoch": 0.57,
1920
+ "grad_norm": 0.6201476454734802,
1921
+ "learning_rate": 8.15273943982811e-05,
1922
+ "loss": 1.6252,
1923
+ "step": 270
1924
+ },
1925
+ {
1926
+ "epoch": 0.57,
1927
+ "grad_norm": 0.8065648674964905,
1928
+ "learning_rate": 8.086383695268938e-05,
1929
+ "loss": 1.0879,
1930
+ "step": 271
1931
+ },
1932
+ {
1933
+ "epoch": 0.57,
1934
+ "grad_norm": 0.40957608819007874,
1935
+ "learning_rate": 8.020115297520093e-05,
1936
+ "loss": 1.4822,
1937
+ "step": 272
1938
+ },
1939
+ {
1940
+ "epoch": 0.57,
1941
+ "grad_norm": 2.3640942573547363,
1942
+ "learning_rate": 7.953937271395464e-05,
1943
+ "loss": 1.4912,
1944
+ "step": 273
1945
+ },
1946
+ {
1947
+ "epoch": 0.58,
1948
+ "grad_norm": 1.3901112079620361,
1949
+ "learning_rate": 7.887852637583926e-05,
1950
+ "loss": 1.2811,
1951
+ "step": 274
1952
+ },
1953
+ {
1954
+ "epoch": 0.58,
1955
+ "grad_norm": 0.41163328289985657,
1956
+ "learning_rate": 7.821864412511485e-05,
1957
+ "loss": 1.4811,
1958
+ "step": 275
1959
+ },
1960
+ {
1961
+ "epoch": 0.58,
1962
+ "grad_norm": 0.8646697402000427,
1963
+ "learning_rate": 7.755975608203572e-05,
1964
+ "loss": 1.1372,
1965
+ "step": 276
1966
+ },
1967
+ {
1968
+ "epoch": 0.58,
1969
+ "grad_norm": 0.7892725467681885,
1970
+ "learning_rate": 7.690189232147566e-05,
1971
+ "loss": 1.239,
1972
+ "step": 277
1973
+ },
1974
+ {
1975
+ "epoch": 0.59,
1976
+ "grad_norm": 1.0216518640518188,
1977
+ "learning_rate": 7.624508287155533e-05,
1978
+ "loss": 1.9391,
1979
+ "step": 278
1980
+ },
1981
+ {
1982
+ "epoch": 0.59,
1983
+ "grad_norm": 0.6296453475952148,
1984
+ "learning_rate": 7.558935771227129e-05,
1985
+ "loss": 1.283,
1986
+ "step": 279
1987
+ },
1988
+ {
1989
+ "epoch": 0.59,
1990
+ "grad_norm": 0.7754496335983276,
1991
+ "learning_rate": 7.493474677412794e-05,
1992
+ "loss": 1.5106,
1993
+ "step": 280
1994
+ },
1995
+ {
1996
+ "epoch": 0.59,
1997
+ "grad_norm": 0.9793290495872498,
1998
+ "learning_rate": 7.428127993677115e-05,
1999
+ "loss": 1.6032,
2000
+ "step": 281
2001
+ },
2002
+ {
2003
+ "epoch": 0.59,
2004
+ "grad_norm": 0.9508350491523743,
2005
+ "learning_rate": 7.362898702762433e-05,
2006
+ "loss": 1.4869,
2007
+ "step": 282
2008
+ },
2009
+ {
2010
+ "epoch": 0.6,
2011
+ "grad_norm": 0.551931619644165,
2012
+ "learning_rate": 7.297789782052717e-05,
2013
+ "loss": 1.268,
2014
+ "step": 283
2015
+ },
2016
+ {
2017
+ "epoch": 0.6,
2018
+ "grad_norm": 0.45385247468948364,
2019
+ "learning_rate": 7.232804203437644e-05,
2020
+ "loss": 1.0128,
2021
+ "step": 284
2022
+ },
2023
+ {
2024
+ "epoch": 0.6,
2025
+ "grad_norm": 0.7140306830406189,
2026
+ "learning_rate": 7.16794493317696e-05,
2027
+ "loss": 1.24,
2028
+ "step": 285
2029
+ },
2030
+ {
2031
+ "epoch": 0.6,
2032
+ "grad_norm": 5.549449920654297,
2033
+ "learning_rate": 7.10321493176508e-05,
2034
+ "loss": 1.6162,
2035
+ "step": 286
2036
+ },
2037
+ {
2038
+ "epoch": 0.6,
2039
+ "grad_norm": 1.3684600591659546,
2040
+ "learning_rate": 7.038617153795948e-05,
2041
+ "loss": 1.8522,
2042
+ "step": 287
2043
+ },
2044
+ {
2045
+ "epoch": 0.61,
2046
+ "grad_norm": 0.850640058517456,
2047
+ "learning_rate": 6.974154547828191e-05,
2048
+ "loss": 1.9203,
2049
+ "step": 288
2050
+ },
2051
+ {
2052
+ "epoch": 0.61,
2053
+ "grad_norm": 0.7197821140289307,
2054
+ "learning_rate": 6.909830056250527e-05,
2055
+ "loss": 1.2131,
2056
+ "step": 289
2057
+ },
2058
+ {
2059
+ "epoch": 0.61,
2060
+ "grad_norm": 0.7707614898681641,
2061
+ "learning_rate": 6.845646615147445e-05,
2062
+ "loss": 1.7302,
2063
+ "step": 290
2064
+ },
2065
+ {
2066
+ "epoch": 0.61,
2067
+ "grad_norm": 0.7183483242988586,
2068
+ "learning_rate": 6.781607154165218e-05,
2069
+ "loss": 0.676,
2070
+ "step": 291
2071
+ },
2072
+ {
2073
+ "epoch": 0.61,
2074
+ "grad_norm": 2.40576171875,
2075
+ "learning_rate": 6.717714596378137e-05,
2076
+ "loss": 1.399,
2077
+ "step": 292
2078
+ },
2079
+ {
2080
+ "epoch": 0.62,
2081
+ "grad_norm": 0.5833460688591003,
2082
+ "learning_rate": 6.653971858155141e-05,
2083
+ "loss": 1.3112,
2084
+ "step": 293
2085
+ },
2086
+ {
2087
+ "epoch": 0.62,
2088
+ "grad_norm": 1.4274028539657593,
2089
+ "learning_rate": 6.590381849026655e-05,
2090
+ "loss": 1.7495,
2091
+ "step": 294
2092
+ },
2093
+ {
2094
+ "epoch": 0.62,
2095
+ "grad_norm": 0.43348875641822815,
2096
+ "learning_rate": 6.526947471551798e-05,
2097
+ "loss": 1.5504,
2098
+ "step": 295
2099
+ },
2100
+ {
2101
+ "epoch": 0.62,
2102
+ "grad_norm": 0.9081869721412659,
2103
+ "learning_rate": 6.463671621185908e-05,
2104
+ "loss": 1.0873,
2105
+ "step": 296
2106
+ },
2107
+ {
2108
+ "epoch": 0.63,
2109
+ "grad_norm": 1.0856722593307495,
2110
+ "learning_rate": 6.40055718614837e-05,
2111
+ "loss": 1.2858,
2112
+ "step": 297
2113
+ },
2114
+ {
2115
+ "epoch": 0.63,
2116
+ "grad_norm": 0.3667042851448059,
2117
+ "learning_rate": 6.337607047290774e-05,
2118
+ "loss": 1.1236,
2119
+ "step": 298
2120
+ },
2121
+ {
2122
+ "epoch": 0.63,
2123
+ "grad_norm": 1.053734540939331,
2124
+ "learning_rate": 6.274824077965438e-05,
2125
+ "loss": 1.0311,
2126
+ "step": 299
2127
+ },
2128
+ {
2129
+ "epoch": 0.63,
2130
+ "grad_norm": 0.639960765838623,
2131
+ "learning_rate": 6.21221114389424e-05,
2132
+ "loss": 1.2877,
2133
+ "step": 300
2134
+ },
2135
+ {
2136
+ "epoch": 0.63,
2137
+ "grad_norm": 0.3543897569179535,
2138
+ "learning_rate": 6.149771103037821e-05,
2139
+ "loss": 1.2895,
2140
+ "step": 301
2141
+ },
2142
+ {
2143
+ "epoch": 0.64,
2144
+ "grad_norm": 0.5615779161453247,
2145
+ "learning_rate": 6.0875068054651266e-05,
2146
+ "loss": 1.3834,
2147
+ "step": 302
2148
+ },
2149
+ {
2150
+ "epoch": 0.64,
2151
+ "grad_norm": 0.6555135846138,
2152
+ "learning_rate": 6.0254210932233176e-05,
2153
+ "loss": 1.1616,
2154
+ "step": 303
2155
+ },
2156
+ {
2157
+ "epoch": 0.64,
2158
+ "grad_norm": 0.647588312625885,
2159
+ "learning_rate": 5.9635168002080564e-05,
2160
+ "loss": 1.3614,
2161
+ "step": 304
2162
+ },
2163
+ {
2164
+ "epoch": 0.64,
2165
+ "grad_norm": 0.6642404794692993,
2166
+ "learning_rate": 5.901796752034128e-05,
2167
+ "loss": 1.321,
2168
+ "step": 305
2169
+ },
2170
+ {
2171
+ "epoch": 0.64,
2172
+ "grad_norm": 0.41330766677856445,
2173
+ "learning_rate": 5.8402637659064895e-05,
2174
+ "loss": 1.1208,
2175
+ "step": 306
2176
+ },
2177
+ {
2178
+ "epoch": 0.65,
2179
+ "grad_norm": 0.7018295526504517,
2180
+ "learning_rate": 5.7789206504916816e-05,
2181
+ "loss": 1.408,
2182
+ "step": 307
2183
+ },
2184
+ {
2185
+ "epoch": 0.65,
2186
+ "grad_norm": 0.5185045599937439,
2187
+ "learning_rate": 5.717770205789601e-05,
2188
+ "loss": 1.2841,
2189
+ "step": 308
2190
+ },
2191
+ {
2192
+ "epoch": 0.65,
2193
+ "grad_norm": 0.5689573287963867,
2194
+ "learning_rate": 5.656815223005714e-05,
2195
+ "loss": 0.8656,
2196
+ "step": 309
2197
+ },
2198
+ {
2199
+ "epoch": 0.65,
2200
+ "grad_norm": 2.1489999294281006,
2201
+ "learning_rate": 5.596058484423656e-05,
2202
+ "loss": 1.0203,
2203
+ "step": 310
2204
+ },
2205
+ {
2206
+ "epoch": 0.65,
2207
+ "grad_norm": 0.6517840027809143,
2208
+ "learning_rate": 5.535502763278222e-05,
2209
+ "loss": 1.2159,
2210
+ "step": 311
2211
+ },
2212
+ {
2213
+ "epoch": 0.66,
2214
+ "grad_norm": 0.47839996218681335,
2215
+ "learning_rate": 5.4751508236287865e-05,
2216
+ "loss": 0.9904,
2217
+ "step": 312
2218
+ },
2219
+ {
2220
+ "epoch": 0.66,
2221
+ "grad_norm": 0.5880618691444397,
2222
+ "learning_rate": 5.415005420233141e-05,
2223
+ "loss": 0.6293,
2224
+ "step": 313
2225
+ },
2226
+ {
2227
+ "epoch": 0.66,
2228
+ "grad_norm": 0.8745140433311462,
2229
+ "learning_rate": 5.355069298421747e-05,
2230
+ "loss": 0.9696,
2231
+ "step": 314
2232
+ },
2233
+ {
2234
+ "epoch": 0.66,
2235
+ "grad_norm": 0.5589584112167358,
2236
+ "learning_rate": 5.2953451939724454e-05,
2237
+ "loss": 0.7707,
2238
+ "step": 315
2239
+ },
2240
+ {
2241
+ "epoch": 0.67,
2242
+ "grad_norm": 0.5342937111854553,
2243
+ "learning_rate": 5.2358358329855516e-05,
2244
+ "loss": 1.0788,
2245
+ "step": 316
2246
+ },
2247
+ {
2248
+ "epoch": 0.67,
2249
+ "grad_norm": 0.537293016910553,
2250
+ "learning_rate": 5.1765439317594466e-05,
2251
+ "loss": 1.4954,
2252
+ "step": 317
2253
+ },
2254
+ {
2255
+ "epoch": 0.67,
2256
+ "grad_norm": 0.48457396030426025,
2257
+ "learning_rate": 5.1174721966665774e-05,
2258
+ "loss": 1.0569,
2259
+ "step": 318
2260
+ },
2261
+ {
2262
+ "epoch": 0.67,
2263
+ "grad_norm": 0.46171680092811584,
2264
+ "learning_rate": 5.058623324029944e-05,
2265
+ "loss": 1.6199,
2266
+ "step": 319
2267
+ },
2268
+ {
2269
+ "epoch": 0.67,
2270
+ "grad_norm": 0.9995810985565186,
2271
+ "learning_rate": 5.000000000000002e-05,
2272
+ "loss": 1.5058,
2273
+ "step": 320
2274
+ },
2275
+ {
2276
+ "epoch": 0.68,
2277
+ "grad_norm": 0.8011060357093811,
2278
+ "learning_rate": 4.941604900432065e-05,
2279
+ "loss": 1.0958,
2280
+ "step": 321
2281
+ },
2282
+ {
2283
+ "epoch": 0.68,
2284
+ "grad_norm": 0.5803133845329285,
2285
+ "learning_rate": 4.8834406907641784e-05,
2286
+ "loss": 0.8619,
2287
+ "step": 322
2288
+ },
2289
+ {
2290
+ "epoch": 0.68,
2291
+ "grad_norm": 1.2584335803985596,
2292
+ "learning_rate": 4.825510025895429e-05,
2293
+ "loss": 1.4993,
2294
+ "step": 323
2295
+ },
2296
+ {
2297
+ "epoch": 0.68,
2298
+ "grad_norm": 0.43015971779823303,
2299
+ "learning_rate": 4.767815550064778e-05,
2300
+ "loss": 0.8414,
2301
+ "step": 324
2302
+ },
2303
+ {
2304
+ "epoch": 0.68,
2305
+ "grad_norm": 1.1480287313461304,
2306
+ "learning_rate": 4.710359896730379e-05,
2307
+ "loss": 1.4084,
2308
+ "step": 325
2309
+ },
2310
+ {
2311
+ "epoch": 0.69,
2312
+ "grad_norm": 0.6011125445365906,
2313
+ "learning_rate": 4.65314568844933e-05,
2314
+ "loss": 0.9027,
2315
+ "step": 326
2316
+ },
2317
+ {
2318
+ "epoch": 0.69,
2319
+ "grad_norm": 0.9287271499633789,
2320
+ "learning_rate": 4.596175536758024e-05,
2321
+ "loss": 1.3626,
2322
+ "step": 327
2323
+ },
2324
+ {
2325
+ "epoch": 0.69,
2326
+ "grad_norm": 0.5835272669792175,
2327
+ "learning_rate": 4.539452042052901e-05,
2328
+ "loss": 0.9265,
2329
+ "step": 328
2330
+ },
2331
+ {
2332
+ "epoch": 0.69,
2333
+ "grad_norm": 0.9826067686080933,
2334
+ "learning_rate": 4.482977793471769e-05,
2335
+ "loss": 0.9542,
2336
+ "step": 329
2337
+ },
2338
+ {
2339
+ "epoch": 0.69,
2340
+ "grad_norm": 0.4515445828437805,
2341
+ "learning_rate": 4.426755368775637e-05,
2342
+ "loss": 1.1758,
2343
+ "step": 330
2344
+ },
2345
+ {
2346
+ "epoch": 0.7,
2347
+ "grad_norm": 0.791499674320221,
2348
+ "learning_rate": 4.3707873342310254e-05,
2349
+ "loss": 0.6814,
2350
+ "step": 331
2351
+ },
2352
+ {
2353
+ "epoch": 0.7,
2354
+ "grad_norm": 0.8545525074005127,
2355
+ "learning_rate": 4.3150762444928473e-05,
2356
+ "loss": 1.4359,
2357
+ "step": 332
2358
+ },
2359
+ {
2360
+ "epoch": 0.7,
2361
+ "grad_norm": 0.8281897306442261,
2362
+ "learning_rate": 4.259624642487805e-05,
2363
+ "loss": 1.5126,
2364
+ "step": 333
2365
+ },
2366
+ {
2367
+ "epoch": 0.7,
2368
+ "grad_norm": 1.3756364583969116,
2369
+ "learning_rate": 4.204435059298303e-05,
2370
+ "loss": 0.8866,
2371
+ "step": 334
2372
+ },
2373
+ {
2374
+ "epoch": 0.71,
2375
+ "grad_norm": 1.1280224323272705,
2376
+ "learning_rate": 4.149510014046922e-05,
2377
+ "loss": 0.9567,
2378
+ "step": 335
2379
+ },
2380
+ {
2381
+ "epoch": 0.71,
2382
+ "grad_norm": 0.3786430060863495,
2383
+ "learning_rate": 4.094852013781456e-05,
2384
+ "loss": 1.2275,
2385
+ "step": 336
2386
+ },
2387
+ {
2388
+ "epoch": 0.71,
2389
+ "grad_norm": 1.3916789293289185,
2390
+ "learning_rate": 4.040463553360431e-05,
2391
+ "loss": 3.2689,
2392
+ "step": 337
2393
+ },
2394
+ {
2395
+ "epoch": 0.71,
2396
+ "grad_norm": 0.828298032283783,
2397
+ "learning_rate": 3.9863471153392804e-05,
2398
+ "loss": 1.0928,
2399
+ "step": 338
2400
+ },
2401
+ {
2402
+ "epoch": 0.71,
2403
+ "grad_norm": 1.3147966861724854,
2404
+ "learning_rate": 3.9325051698569925e-05,
2405
+ "loss": 1.7501,
2406
+ "step": 339
2407
+ },
2408
+ {
2409
+ "epoch": 0.72,
2410
+ "grad_norm": 0.8213374018669128,
2411
+ "learning_rate": 3.878940174523371e-05,
2412
+ "loss": 1.5596,
2413
+ "step": 340
2414
+ },
2415
+ {
2416
+ "epoch": 0.72,
2417
+ "grad_norm": 2.037734270095825,
2418
+ "learning_rate": 3.8256545743068725e-05,
2419
+ "loss": 1.3332,
2420
+ "step": 341
2421
+ },
2422
+ {
2423
+ "epoch": 0.72,
2424
+ "grad_norm": 0.9790574908256531,
2425
+ "learning_rate": 3.772650801422982e-05,
2426
+ "loss": 1.0873,
2427
+ "step": 342
2428
+ },
2429
+ {
2430
+ "epoch": 0.72,
2431
+ "grad_norm": 0.4515441954135895,
2432
+ "learning_rate": 3.719931275223205e-05,
2433
+ "loss": 1.3623,
2434
+ "step": 343
2435
+ },
2436
+ {
2437
+ "epoch": 0.72,
2438
+ "grad_norm": 0.9941519498825073,
2439
+ "learning_rate": 3.6674984020846504e-05,
2440
+ "loss": 1.0522,
2441
+ "step": 344
2442
+ },
2443
+ {
2444
+ "epoch": 0.73,
2445
+ "grad_norm": 0.93306565284729,
2446
+ "learning_rate": 3.615354575300166e-05,
2447
+ "loss": 1.5876,
2448
+ "step": 345
2449
+ },
2450
+ {
2451
+ "epoch": 0.73,
2452
+ "grad_norm": 2.297698497772217,
2453
+ "learning_rate": 3.5635021749691166e-05,
2454
+ "loss": 0.8665,
2455
+ "step": 346
2456
+ },
2457
+ {
2458
+ "epoch": 0.73,
2459
+ "grad_norm": 0.9025039076805115,
2460
+ "learning_rate": 3.511943567888732e-05,
2461
+ "loss": 0.4777,
2462
+ "step": 347
2463
+ },
2464
+ {
2465
+ "epoch": 0.73,
2466
+ "grad_norm": 0.38800546526908875,
2467
+ "learning_rate": 3.460681107446091e-05,
2468
+ "loss": 0.8782,
2469
+ "step": 348
2470
+ },
2471
+ {
2472
+ "epoch": 0.73,
2473
+ "grad_norm": 1.42990243434906,
2474
+ "learning_rate": 3.4097171335106824e-05,
2475
+ "loss": 1.1503,
2476
+ "step": 349
2477
+ },
2478
+ {
2479
+ "epoch": 0.74,
2480
+ "grad_norm": 0.4309168756008148,
2481
+ "learning_rate": 3.3590539723276083e-05,
2482
+ "loss": 1.4906,
2483
+ "step": 350
2484
+ },
2485
+ {
2486
+ "epoch": 0.74,
2487
+ "grad_norm": 1.5898098945617676,
2488
+ "learning_rate": 3.308693936411421e-05,
2489
+ "loss": 1.2899,
2490
+ "step": 351
2491
+ },
2492
+ {
2493
+ "epoch": 0.74,
2494
+ "grad_norm": 0.8075172305107117,
2495
+ "learning_rate": 3.258639324440527e-05,
2496
+ "loss": 0.7296,
2497
+ "step": 352
2498
+ },
2499
+ {
2500
+ "epoch": 0.74,
2501
+ "grad_norm": 0.7422662973403931,
2502
+ "learning_rate": 3.2088924211523144e-05,
2503
+ "loss": 1.5174,
2504
+ "step": 353
2505
+ },
2506
+ {
2507
+ "epoch": 0.75,
2508
+ "grad_norm": 0.38478884100914,
2509
+ "learning_rate": 3.1594554972388265e-05,
2510
+ "loss": 1.3737,
2511
+ "step": 354
2512
+ },
2513
+ {
2514
+ "epoch": 0.75,
2515
+ "grad_norm": 0.49486249685287476,
2516
+ "learning_rate": 3.110330809243134e-05,
2517
+ "loss": 1.3679,
2518
+ "step": 355
2519
+ },
2520
+ {
2521
+ "epoch": 0.75,
2522
+ "grad_norm": 0.4216090738773346,
2523
+ "learning_rate": 3.061520599456341e-05,
2524
+ "loss": 1.3637,
2525
+ "step": 356
2526
+ },
2527
+ {
2528
+ "epoch": 0.75,
2529
+ "grad_norm": 0.46424904465675354,
2530
+ "learning_rate": 3.0130270958152197e-05,
2531
+ "loss": 1.3429,
2532
+ "step": 357
2533
+ },
2534
+ {
2535
+ "epoch": 0.75,
2536
+ "eval_loss": 1.2427868843078613,
2537
+ "eval_runtime": 10.4613,
2538
+ "eval_samples_per_second": 9.559,
2539
+ "eval_steps_per_second": 9.559,
2540
+ "step": 357
2541
+ },
2542
+ {
2543
+ "epoch": 0.75,
2544
+ "grad_norm": 1.1968390941619873,
2545
+ "learning_rate": 2.964852511800519e-05,
2546
+ "loss": 1.3649,
2547
+ "step": 358
2548
+ },
2549
+ {
2550
+ "epoch": 0.76,
2551
+ "grad_norm": 0.45987701416015625,
2552
+ "learning_rate": 2.9169990463359555e-05,
2553
+ "loss": 1.4336,
2554
+ "step": 359
2555
+ },
2556
+ {
2557
+ "epoch": 0.76,
2558
+ "grad_norm": 0.5114177465438843,
2559
+ "learning_rate": 2.869468883687798e-05,
2560
+ "loss": 1.4723,
2561
+ "step": 360
2562
+ },
2563
+ {
2564
+ "epoch": 0.76,
2565
+ "grad_norm": 0.3620365560054779,
2566
+ "learning_rate": 2.8222641933652117e-05,
2567
+ "loss": 1.6468,
2568
+ "step": 361
2569
+ },
2570
+ {
2571
+ "epoch": 0.76,
2572
+ "grad_norm": 0.9834029078483582,
2573
+ "learning_rate": 2.7753871300212142e-05,
2574
+ "loss": 0.963,
2575
+ "step": 362
2576
+ },
2577
+ {
2578
+ "epoch": 0.76,
2579
+ "grad_norm": 0.6030866503715515,
2580
+ "learning_rate": 2.7288398333543064e-05,
2581
+ "loss": 1.1532,
2582
+ "step": 363
2583
+ },
2584
+ {
2585
+ "epoch": 0.77,
2586
+ "grad_norm": 0.7282407879829407,
2587
+ "learning_rate": 2.6826244280108437e-05,
2588
+ "loss": 1.2677,
2589
+ "step": 364
2590
+ },
2591
+ {
2592
+ "epoch": 0.77,
2593
+ "grad_norm": 0.549340009689331,
2594
+ "learning_rate": 2.6367430234880284e-05,
2595
+ "loss": 1.1274,
2596
+ "step": 365
2597
+ },
2598
+ {
2599
+ "epoch": 0.77,
2600
+ "grad_norm": 0.6679304838180542,
2601
+ "learning_rate": 2.591197714037631e-05,
2602
+ "loss": 1.5468,
2603
+ "step": 366
2604
+ },
2605
+ {
2606
+ "epoch": 0.77,
2607
+ "grad_norm": 0.3590414822101593,
2608
+ "learning_rate": 2.5459905785704042e-05,
2609
+ "loss": 1.7081,
2610
+ "step": 367
2611
+ },
2612
+ {
2613
+ "epoch": 0.77,
2614
+ "grad_norm": 0.8412752747535706,
2615
+ "learning_rate": 2.5011236805611814e-05,
2616
+ "loss": 1.3058,
2617
+ "step": 368
2618
+ },
2619
+ {
2620
+ "epoch": 0.78,
2621
+ "grad_norm": 1.4232923984527588,
2622
+ "learning_rate": 2.4565990679546914e-05,
2623
+ "loss": 1.3649,
2624
+ "step": 369
2625
+ },
2626
+ {
2627
+ "epoch": 0.78,
2628
+ "grad_norm": 0.7082968950271606,
2629
+ "learning_rate": 2.4124187730720917e-05,
2630
+ "loss": 1.3421,
2631
+ "step": 370
2632
+ },
2633
+ {
2634
+ "epoch": 0.78,
2635
+ "grad_norm": 0.8737981915473938,
2636
+ "learning_rate": 2.368584812518184e-05,
2637
+ "loss": 0.8252,
2638
+ "step": 371
2639
+ },
2640
+ {
2641
+ "epoch": 0.78,
2642
+ "grad_norm": 0.6763678193092346,
2643
+ "learning_rate": 2.3250991870893835e-05,
2644
+ "loss": 1.8269,
2645
+ "step": 372
2646
+ },
2647
+ {
2648
+ "epoch": 0.79,
2649
+ "grad_norm": 0.49625009298324585,
2650
+ "learning_rate": 2.2819638816823797e-05,
2651
+ "loss": 1.7375,
2652
+ "step": 373
2653
+ },
2654
+ {
2655
+ "epoch": 0.79,
2656
+ "grad_norm": 1.235646367073059,
2657
+ "learning_rate": 2.2391808652035517e-05,
2658
+ "loss": 1.0455,
2659
+ "step": 374
2660
+ },
2661
+ {
2662
+ "epoch": 0.79,
2663
+ "grad_norm": 0.6838667988777161,
2664
+ "learning_rate": 2.1967520904790827e-05,
2665
+ "loss": 1.2117,
2666
+ "step": 375
2667
+ },
2668
+ {
2669
+ "epoch": 0.79,
2670
+ "grad_norm": 0.5402644872665405,
2671
+ "learning_rate": 2.154679494165829e-05,
2672
+ "loss": 1.4113,
2673
+ "step": 376
2674
+ },
2675
+ {
2676
+ "epoch": 0.79,
2677
+ "grad_norm": 0.9066751599311829,
2678
+ "learning_rate": 2.1129649966629184e-05,
2679
+ "loss": 1.1857,
2680
+ "step": 377
2681
+ },
2682
+ {
2683
+ "epoch": 0.8,
2684
+ "grad_norm": 1.1335337162017822,
2685
+ "learning_rate": 2.0716105020241072e-05,
2686
+ "loss": 1.4199,
2687
+ "step": 378
2688
+ },
2689
+ {
2690
+ "epoch": 0.8,
2691
+ "grad_norm": 0.7712799310684204,
2692
+ "learning_rate": 2.0306178978708514e-05,
2693
+ "loss": 1.7568,
2694
+ "step": 379
2695
+ },
2696
+ {
2697
+ "epoch": 0.8,
2698
+ "grad_norm": 0.3476005494594574,
2699
+ "learning_rate": 1.9899890553061562e-05,
2700
+ "loss": 1.4962,
2701
+ "step": 380
2702
+ },
2703
+ {
2704
+ "epoch": 0.8,
2705
+ "grad_norm": 0.7450062036514282,
2706
+ "learning_rate": 1.9497258288291654e-05,
2707
+ "loss": 1.5029,
2708
+ "step": 381
2709
+ },
2710
+ {
2711
+ "epoch": 0.8,
2712
+ "grad_norm": 0.9961157441139221,
2713
+ "learning_rate": 1.9098300562505266e-05,
2714
+ "loss": 1.2156,
2715
+ "step": 382
2716
+ },
2717
+ {
2718
+ "epoch": 0.81,
2719
+ "grad_norm": 0.5865272283554077,
2720
+ "learning_rate": 1.8703035586084816e-05,
2721
+ "loss": 0.8954,
2722
+ "step": 383
2723
+ },
2724
+ {
2725
+ "epoch": 0.81,
2726
+ "grad_norm": 0.7002312541007996,
2727
+ "learning_rate": 1.831148140085762e-05,
2728
+ "loss": 1.3208,
2729
+ "step": 384
2730
+ },
2731
+ {
2732
+ "epoch": 0.81,
2733
+ "grad_norm": 0.5696095824241638,
2734
+ "learning_rate": 1.7923655879272393e-05,
2735
+ "loss": 1.6606,
2736
+ "step": 385
2737
+ },
2738
+ {
2739
+ "epoch": 0.81,
2740
+ "grad_norm": 0.6654199361801147,
2741
+ "learning_rate": 1.753957672358324e-05,
2742
+ "loss": 1.0694,
2743
+ "step": 386
2744
+ },
2745
+ {
2746
+ "epoch": 0.81,
2747
+ "grad_norm": 0.4102238714694977,
2748
+ "learning_rate": 1.7159261465041952e-05,
2749
+ "loss": 1.2681,
2750
+ "step": 387
2751
+ },
2752
+ {
2753
+ "epoch": 0.82,
2754
+ "grad_norm": 0.5439934134483337,
2755
+ "learning_rate": 1.6782727463097624e-05,
2756
+ "loss": 1.018,
2757
+ "step": 388
2758
+ },
2759
+ {
2760
+ "epoch": 0.82,
2761
+ "grad_norm": 1.4591739177703857,
2762
+ "learning_rate": 1.6409991904604173e-05,
2763
+ "loss": 0.8686,
2764
+ "step": 389
2765
+ },
2766
+ {
2767
+ "epoch": 0.82,
2768
+ "grad_norm": 0.4289948046207428,
2769
+ "learning_rate": 1.60410718030361e-05,
2770
+ "loss": 1.1516,
2771
+ "step": 390
2772
+ },
2773
+ {
2774
+ "epoch": 0.82,
2775
+ "grad_norm": 0.46624648571014404,
2776
+ "learning_rate": 1.5675983997711795e-05,
2777
+ "loss": 1.3106,
2778
+ "step": 391
2779
+ },
2780
+ {
2781
+ "epoch": 0.83,
2782
+ "grad_norm": 0.7769433259963989,
2783
+ "learning_rate": 1.5314745153024766e-05,
2784
+ "loss": 1.205,
2785
+ "step": 392
2786
+ },
2787
+ {
2788
+ "epoch": 0.83,
2789
+ "grad_norm": 0.6348716020584106,
2790
+ "learning_rate": 1.495737175768326e-05,
2791
+ "loss": 1.0937,
2792
+ "step": 393
2793
+ },
2794
+ {
2795
+ "epoch": 0.83,
2796
+ "grad_norm": 1.4135714769363403,
2797
+ "learning_rate": 1.4603880123957447e-05,
2798
+ "loss": 1.0782,
2799
+ "step": 394
2800
+ },
2801
+ {
2802
+ "epoch": 0.83,
2803
+ "grad_norm": 0.7596187591552734,
2804
+ "learning_rate": 1.425428638693489e-05,
2805
+ "loss": 1.6273,
2806
+ "step": 395
2807
+ },
2808
+ {
2809
+ "epoch": 0.83,
2810
+ "grad_norm": 1.391519546508789,
2811
+ "learning_rate": 1.3908606503784139e-05,
2812
+ "loss": 1.4292,
2813
+ "step": 396
2814
+ },
2815
+ {
2816
+ "epoch": 0.84,
2817
+ "grad_norm": 1.8692115545272827,
2818
+ "learning_rate": 1.356685625302625e-05,
2819
+ "loss": 0.5871,
2820
+ "step": 397
2821
+ },
2822
+ {
2823
+ "epoch": 0.84,
2824
+ "grad_norm": 0.47545358538627625,
2825
+ "learning_rate": 1.3229051233814637e-05,
2826
+ "loss": 1.0054,
2827
+ "step": 398
2828
+ },
2829
+ {
2830
+ "epoch": 0.84,
2831
+ "grad_norm": 0.2672554552555084,
2832
+ "learning_rate": 1.2895206865223064e-05,
2833
+ "loss": 0.6172,
2834
+ "step": 399
2835
+ },
2836
+ {
2837
+ "epoch": 0.84,
2838
+ "grad_norm": 0.6463977694511414,
2839
+ "learning_rate": 1.2565338385541792e-05,
2840
+ "loss": 2.0793,
2841
+ "step": 400
2842
+ },
2843
+ {
2844
+ "epoch": 0.84,
2845
+ "grad_norm": 0.5812274813652039,
2846
+ "learning_rate": 1.2239460851582118e-05,
2847
+ "loss": 0.8392,
2848
+ "step": 401
2849
+ },
2850
+ {
2851
+ "epoch": 0.85,
2852
+ "grad_norm": 1.5981879234313965,
2853
+ "learning_rate": 1.1917589137989005e-05,
2854
+ "loss": 1.459,
2855
+ "step": 402
2856
+ },
2857
+ {
2858
+ "epoch": 0.85,
2859
+ "grad_norm": 0.9397989511489868,
2860
+ "learning_rate": 1.1599737936562149e-05,
2861
+ "loss": 1.3638,
2862
+ "step": 403
2863
+ },
2864
+ {
2865
+ "epoch": 0.85,
2866
+ "grad_norm": 0.3462386429309845,
2867
+ "learning_rate": 1.1285921755585504e-05,
2868
+ "loss": 1.1605,
2869
+ "step": 404
2870
+ },
2871
+ {
2872
+ "epoch": 0.85,
2873
+ "grad_norm": 1.203017234802246,
2874
+ "learning_rate": 1.097615491916485e-05,
2875
+ "loss": 1.5022,
2876
+ "step": 405
2877
+ },
2878
+ {
2879
+ "epoch": 0.85,
2880
+ "grad_norm": 0.7160519957542419,
2881
+ "learning_rate": 1.0670451566574102e-05,
2882
+ "loss": 1.0726,
2883
+ "step": 406
2884
+ },
2885
+ {
2886
+ "epoch": 0.86,
2887
+ "grad_norm": 0.9885064959526062,
2888
+ "learning_rate": 1.0368825651609893e-05,
2889
+ "loss": 1.0344,
2890
+ "step": 407
2891
+ },
2892
+ {
2893
+ "epoch": 0.86,
2894
+ "grad_norm": 1.1007866859436035,
2895
+ "learning_rate": 1.007129094195468e-05,
2896
+ "loss": 1.4191,
2897
+ "step": 408
2898
+ },
2899
+ {
2900
+ "epoch": 0.86,
2901
+ "grad_norm": 1.0664376020431519,
2902
+ "learning_rate": 9.777861018548251e-06,
2903
+ "loss": 1.8957,
2904
+ "step": 409
2905
+ },
2906
+ {
2907
+ "epoch": 0.86,
2908
+ "grad_norm": 1.2938302755355835,
2909
+ "learning_rate": 9.488549274967872e-06,
2910
+ "loss": 1.181,
2911
+ "step": 410
2912
+ },
2913
+ {
2914
+ "epoch": 0.87,
2915
+ "grad_norm": 0.7518212199211121,
2916
+ "learning_rate": 9.203368916817012e-06,
2917
+ "loss": 1.4975,
2918
+ "step": 411
2919
+ },
2920
+ {
2921
+ "epoch": 0.87,
2922
+ "grad_norm": 1.3200393915176392,
2923
+ "learning_rate": 8.92233296112236e-06,
2924
+ "loss": 1.0157,
2925
+ "step": 412
2926
+ },
2927
+ {
2928
+ "epoch": 0.87,
2929
+ "grad_norm": 0.677116334438324,
2930
+ "learning_rate": 8.645454235739903e-06,
2931
+ "loss": 1.1984,
2932
+ "step": 413
2933
+ },
2934
+ {
2935
+ "epoch": 0.87,
2936
+ "grad_norm": 0.9666435122489929,
2937
+ "learning_rate": 8.372745378769309e-06,
2938
+ "loss": 1.1112,
2939
+ "step": 414
2940
+ },
2941
+ {
2942
+ "epoch": 0.87,
2943
+ "grad_norm": 0.8352184295654297,
2944
+ "learning_rate": 8.10421883797694e-06,
2945
+ "loss": 1.0512,
2946
+ "step": 415
2947
+ },
2948
+ {
2949
+ "epoch": 0.88,
2950
+ "grad_norm": 2.5026190280914307,
2951
+ "learning_rate": 7.839886870227909e-06,
2952
+ "loss": 1.1279,
2953
+ "step": 416
2954
+ },
2955
+ {
2956
+ "epoch": 0.88,
2957
+ "grad_norm": 0.36853912472724915,
2958
+ "learning_rate": 7.5797615409264335e-06,
2959
+ "loss": 1.1051,
2960
+ "step": 417
2961
+ },
2962
+ {
2963
+ "epoch": 0.88,
2964
+ "grad_norm": 0.5076872110366821,
2965
+ "learning_rate": 7.32385472346514e-06,
2966
+ "loss": 1.597,
2967
+ "step": 418
2968
+ },
2969
+ {
2970
+ "epoch": 0.88,
2971
+ "grad_norm": 0.9718438982963562,
2972
+ "learning_rate": 7.072178098683246e-06,
2973
+ "loss": 1.1807,
2974
+ "step": 419
2975
+ },
2976
+ {
2977
+ "epoch": 0.88,
2978
+ "grad_norm": 0.5310528874397278,
2979
+ "learning_rate": 6.824743154333157e-06,
2980
+ "loss": 1.2764,
2981
+ "step": 420
2982
+ },
2983
+ {
2984
+ "epoch": 0.89,
2985
+ "grad_norm": 0.9790662527084351,
2986
+ "learning_rate": 6.581561184556295e-06,
2987
+ "loss": 1.5014,
2988
+ "step": 421
2989
+ },
2990
+ {
2991
+ "epoch": 0.89,
2992
+ "grad_norm": 2.499530553817749,
2993
+ "learning_rate": 6.342643289367522e-06,
2994
+ "loss": 1.3249,
2995
+ "step": 422
2996
+ },
2997
+ {
2998
+ "epoch": 0.89,
2999
+ "grad_norm": 0.6649277210235596,
3000
+ "learning_rate": 6.108000374148448e-06,
3001
+ "loss": 1.432,
3002
+ "step": 423
3003
+ },
3004
+ {
3005
+ "epoch": 0.89,
3006
+ "grad_norm": 0.8835659623146057,
3007
+ "learning_rate": 5.87764314914967e-06,
3008
+ "loss": 1.0439,
3009
+ "step": 424
3010
+ },
3011
+ {
3012
+ "epoch": 0.89,
3013
+ "grad_norm": 0.7555325627326965,
3014
+ "learning_rate": 5.651582129001986e-06,
3015
+ "loss": 0.9622,
3016
+ "step": 425
3017
+ },
3018
+ {
3019
+ "epoch": 0.9,
3020
+ "grad_norm": 0.9321297407150269,
3021
+ "learning_rate": 5.429827632236284e-06,
3022
+ "loss": 1.1174,
3023
+ "step": 426
3024
+ },
3025
+ {
3026
+ "epoch": 0.9,
3027
+ "grad_norm": 0.7446428537368774,
3028
+ "learning_rate": 5.212389780812732e-06,
3029
+ "loss": 1.2175,
3030
+ "step": 427
3031
+ },
3032
+ {
3033
+ "epoch": 0.9,
3034
+ "grad_norm": 0.4157393276691437,
3035
+ "learning_rate": 4.999278499658666e-06,
3036
+ "loss": 1.3221,
3037
+ "step": 428
3038
+ },
3039
+ {
3040
+ "epoch": 0.9,
3041
+ "grad_norm": 0.4439353048801422,
3042
+ "learning_rate": 4.790503516215572e-06,
3043
+ "loss": 1.3804,
3044
+ "step": 429
3045
+ },
3046
+ {
3047
+ "epoch": 0.91,
3048
+ "grad_norm": 0.6780000329017639,
3049
+ "learning_rate": 4.586074359995119e-06,
3050
+ "loss": 1.5498,
3051
+ "step": 430
3052
+ },
3053
+ {
3054
+ "epoch": 0.91,
3055
+ "grad_norm": 0.6816204190254211,
3056
+ "learning_rate": 4.386000362144138e-06,
3057
+ "loss": 0.8413,
3058
+ "step": 431
3059
+ },
3060
+ {
3061
+ "epoch": 0.91,
3062
+ "grad_norm": 0.4683542847633362,
3063
+ "learning_rate": 4.190290655018736e-06,
3064
+ "loss": 1.5352,
3065
+ "step": 432
3066
+ },
3067
+ {
3068
+ "epoch": 0.91,
3069
+ "grad_norm": 0.4905780553817749,
3070
+ "learning_rate": 3.998954171767422e-06,
3071
+ "loss": 1.5878,
3072
+ "step": 433
3073
+ },
3074
+ {
3075
+ "epoch": 0.91,
3076
+ "grad_norm": 0.6626597046852112,
3077
+ "learning_rate": 3.811999645923414e-06,
3078
+ "loss": 1.5102,
3079
+ "step": 434
3080
+ },
3081
+ {
3082
+ "epoch": 0.92,
3083
+ "grad_norm": 0.5728758573532104,
3084
+ "learning_rate": 3.6294356110059157e-06,
3085
+ "loss": 1.3155,
3086
+ "step": 435
3087
+ },
3088
+ {
3089
+ "epoch": 0.92,
3090
+ "grad_norm": 0.9096332788467407,
3091
+ "learning_rate": 3.451270400130646e-06,
3092
+ "loss": 1.5012,
3093
+ "step": 436
3094
+ },
3095
+ {
3096
+ "epoch": 0.92,
3097
+ "grad_norm": 0.9138293266296387,
3098
+ "learning_rate": 3.277512145629502e-06,
3099
+ "loss": 1.0071,
3100
+ "step": 437
3101
+ },
3102
+ {
3103
+ "epoch": 0.92,
3104
+ "grad_norm": 0.7803674340248108,
3105
+ "learning_rate": 3.10816877867931e-06,
3106
+ "loss": 1.1,
3107
+ "step": 438
3108
+ },
3109
+ {
3110
+ "epoch": 0.92,
3111
+ "grad_norm": 1.2517226934432983,
3112
+ "learning_rate": 2.943248028939838e-06,
3113
+ "loss": 1.2342,
3114
+ "step": 439
3115
+ },
3116
+ {
3117
+ "epoch": 0.93,
3118
+ "grad_norm": 0.6347147822380066,
3119
+ "learning_rate": 2.7827574242009437e-06,
3120
+ "loss": 1.1261,
3121
+ "step": 440
3122
+ },
3123
+ {
3124
+ "epoch": 0.93,
3125
+ "grad_norm": 0.4368477165699005,
3126
+ "learning_rate": 2.626704290039017e-06,
3127
+ "loss": 1.1669,
3128
+ "step": 441
3129
+ },
3130
+ {
3131
+ "epoch": 0.93,
3132
+ "grad_norm": 0.7963775396347046,
3133
+ "learning_rate": 2.4750957494826033e-06,
3134
+ "loss": 1.3863,
3135
+ "step": 442
3136
+ },
3137
+ {
3138
+ "epoch": 0.93,
3139
+ "grad_norm": 1.0838688611984253,
3140
+ "learning_rate": 2.327938722687184e-06,
3141
+ "loss": 1.1262,
3142
+ "step": 443
3143
+ },
3144
+ {
3145
+ "epoch": 0.93,
3146
+ "grad_norm": 0.48085644841194153,
3147
+ "learning_rate": 2.1852399266194314e-06,
3148
+ "loss": 1.7383,
3149
+ "step": 444
3150
+ },
3151
+ {
3152
+ "epoch": 0.94,
3153
+ "grad_norm": 0.5789294242858887,
3154
+ "learning_rate": 2.0470058747505516e-06,
3155
+ "loss": 1.2789,
3156
+ "step": 445
3157
+ },
3158
+ {
3159
+ "epoch": 0.94,
3160
+ "grad_norm": 1.7602370977401733,
3161
+ "learning_rate": 1.9132428767589473e-06,
3162
+ "loss": 2.2284,
3163
+ "step": 446
3164
+ },
3165
+ {
3166
+ "epoch": 0.94,
3167
+ "grad_norm": 0.6166039109230042,
3168
+ "learning_rate": 1.7839570382422787e-06,
3169
+ "loss": 1.1418,
3170
+ "step": 447
3171
+ },
3172
+ {
3173
+ "epoch": 0.94,
3174
+ "grad_norm": 0.5087316036224365,
3175
+ "learning_rate": 1.6591542604387445e-06,
3176
+ "loss": 0.7367,
3177
+ "step": 448
3178
+ },
3179
+ {
3180
+ "epoch": 0.95,
3181
+ "grad_norm": 4.2447404861450195,
3182
+ "learning_rate": 1.538840239957684e-06,
3183
+ "loss": 2.1703,
3184
+ "step": 449
3185
+ },
3186
+ {
3187
+ "epoch": 0.95,
3188
+ "grad_norm": 0.3775041103363037,
3189
+ "learning_rate": 1.4230204685196203e-06,
3190
+ "loss": 1.4201,
3191
+ "step": 450
3192
+ },
3193
+ {
3194
+ "epoch": 0.95,
3195
+ "grad_norm": 1.3511093854904175,
3196
+ "learning_rate": 1.3117002327055927e-06,
3197
+ "loss": 1.5358,
3198
+ "step": 451
3199
+ },
3200
+ {
3201
+ "epoch": 0.95,
3202
+ "grad_norm": 0.6467747092247009,
3203
+ "learning_rate": 1.20488461371574e-06,
3204
+ "loss": 1.0678,
3205
+ "step": 452
3206
+ },
3207
+ {
3208
+ "epoch": 0.95,
3209
+ "grad_norm": 0.7409128546714783,
3210
+ "learning_rate": 1.102578487137529e-06,
3211
+ "loss": 1.5819,
3212
+ "step": 453
3213
+ },
3214
+ {
3215
+ "epoch": 0.96,
3216
+ "grad_norm": 1.4174960851669312,
3217
+ "learning_rate": 1.004786522723089e-06,
3218
+ "loss": 1.3788,
3219
+ "step": 454
3220
+ },
3221
+ {
3222
+ "epoch": 0.96,
3223
+ "grad_norm": 1.54808509349823,
3224
+ "learning_rate": 9.11513184176116e-07,
3225
+ "loss": 1.1524,
3226
+ "step": 455
3227
+ },
3228
+ {
3229
+ "epoch": 0.96,
3230
+ "grad_norm": 0.3604092299938202,
3231
+ "learning_rate": 8.227627289481121e-07,
3232
+ "loss": 1.246,
3233
+ "step": 456
3234
+ },
3235
+ {
3236
+ "epoch": 0.96,
3237
+ "grad_norm": 1.0738741159439087,
3238
+ "learning_rate": 7.385392080440534e-07,
3239
+ "loss": 0.9884,
3240
+ "step": 457
3241
+ },
3242
+ {
3243
+ "epoch": 0.96,
3244
+ "grad_norm": 1.2032325267791748,
3245
+ "learning_rate": 6.588464658374815e-07,
3246
+ "loss": 2.1638,
3247
+ "step": 458
3248
+ },
3249
+ {
3250
+ "epoch": 0.97,
3251
+ "grad_norm": 0.5337828993797302,
3252
+ "learning_rate": 5.836881398950667e-07,
3253
+ "loss": 1.1283,
3254
+ "step": 459
3255
+ },
3256
+ {
3257
+ "epoch": 0.97,
3258
+ "grad_norm": 1.2100324630737305,
3259
+ "learning_rate": 5.130676608104845e-07,
3260
+ "loss": 1.5026,
3261
+ "step": 460
3262
+ },
3263
+ {
3264
+ "epoch": 0.97,
3265
+ "grad_norm": 1.029868483543396,
3266
+ "learning_rate": 4.469882520479196e-07,
3267
+ "loss": 1.5626,
3268
+ "step": 461
3269
+ },
3270
+ {
3271
+ "epoch": 0.97,
3272
+ "grad_norm": 0.9376425743103027,
3273
+ "learning_rate": 3.8545292979486057e-07,
3274
+ "loss": 1.4563,
3275
+ "step": 462
3276
+ },
3277
+ {
3278
+ "epoch": 0.97,
3279
+ "grad_norm": 0.3371017575263977,
3280
+ "learning_rate": 3.2846450282447703e-07,
3281
+ "loss": 1.0665,
3282
+ "step": 463
3283
+ },
3284
+ {
3285
+ "epoch": 0.98,
3286
+ "grad_norm": 0.8099949359893799,
3287
+ "learning_rate": 2.760255723673888e-07,
3288
+ "loss": 1.0242,
3289
+ "step": 464
3290
+ },
3291
+ {
3292
+ "epoch": 0.98,
3293
+ "grad_norm": 0.5782180428504944,
3294
+ "learning_rate": 2.2813853199292746e-07,
3295
+ "loss": 1.1465,
3296
+ "step": 465
3297
+ },
3298
+ {
3299
+ "epoch": 0.98,
3300
+ "grad_norm": 0.8454908132553101,
3301
+ "learning_rate": 1.8480556749991274e-07,
3302
+ "loss": 1.0718,
3303
+ "step": 466
3304
+ },
3305
+ {
3306
+ "epoch": 0.98,
3307
+ "grad_norm": 1.310767650604248,
3308
+ "learning_rate": 1.460286568168212e-07,
3309
+ "loss": 1.0671,
3310
+ "step": 467
3311
+ },
3312
+ {
3313
+ "epoch": 0.99,
3314
+ "grad_norm": 0.9640721678733826,
3315
+ "learning_rate": 1.1180956991160286e-07,
3316
+ "loss": 0.9314,
3317
+ "step": 468
3318
+ },
3319
+ {
3320
+ "epoch": 0.99,
3321
+ "grad_norm": 1.6716411113739014,
3322
+ "learning_rate": 8.214986871076802e-08,
3323
+ "loss": 1.202,
3324
+ "step": 469
3325
+ },
3326
+ {
3327
+ "epoch": 0.99,
3328
+ "grad_norm": 0.5227134823799133,
3329
+ "learning_rate": 5.705090702819993e-08,
3330
+ "loss": 0.6217,
3331
+ "step": 470
3332
+ },
3333
+ {
3334
+ "epoch": 0.99,
3335
+ "grad_norm": 0.6409493684768677,
3336
+ "learning_rate": 3.6513830503293045e-08,
3337
+ "loss": 1.3795,
3338
+ "step": 471
3339
+ },
3340
+ {
3341
+ "epoch": 0.99,
3342
+ "grad_norm": 0.9884561896324158,
3343
+ "learning_rate": 2.0539576548717076e-08,
3344
+ "loss": 1.0896,
3345
+ "step": 472
3346
+ },
3347
+ {
3348
+ "epoch": 1.0,
3349
+ "grad_norm": 0.44622230529785156,
3350
+ "learning_rate": 9.128874307551272e-09,
3351
+ "loss": 1.4132,
3352
+ "step": 473
3353
+ },
3354
+ {
3355
+ "epoch": 1.0,
3356
+ "grad_norm": 0.5369505286216736,
3357
+ "learning_rate": 2.282244620088747e-09,
3358
+ "loss": 0.7652,
3359
+ "step": 474
3360
+ },
3361
+ {
3362
+ "epoch": 1.0,
3363
+ "grad_norm": 0.6095150709152222,
3364
+ "learning_rate": 0.0,
3365
+ "loss": 1.8662,
3366
+ "step": 475
3367
+ }
3368
+ ],
3369
+ "logging_steps": 1,
3370
+ "max_steps": 475,
3371
+ "num_input_tokens_seen": 0,
3372
+ "num_train_epochs": 1,
3373
+ "save_steps": 500,
3374
+ "total_flos": 777748162805760.0,
3375
+ "train_batch_size": 1,
3376
+ "trial_name": null,
3377
+ "trial_params": null
3378
+ }
checkpoint-475/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c9a1fb5e26ed8821493786ab87117b1dbfd309c2834aae0cc2b1b60637743893
3
+ size 5752
checkpoint-475/vocab.json ADDED
The diff for this file is too large to render. See raw diff
 
config.json ADDED
@@ -0,0 +1,42 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "Qwen/Qwen1.5-0.5B",
3
+ "architectures": [
4
+ "Qwen2ForCausalLM"
5
+ ],
6
+ "attention_dropout": 0.0,
7
+ "eos_token_id": 151643,
8
+ "hidden_act": "silu",
9
+ "hidden_size": 1024,
10
+ "initializer_range": 0.02,
11
+ "intermediate_size": 2816,
12
+ "max_position_embeddings": 32768,
13
+ "max_window_layers": 21,
14
+ "model_type": "qwen2",
15
+ "num_attention_heads": 16,
16
+ "num_hidden_layers": 24,
17
+ "num_key_value_heads": 16,
18
+ "quantization_config": {
19
+ "_load_in_4bit": false,
20
+ "_load_in_8bit": true,
21
+ "bnb_4bit_compute_dtype": "float32",
22
+ "bnb_4bit_quant_storage": "uint8",
23
+ "bnb_4bit_quant_type": "fp4",
24
+ "bnb_4bit_use_double_quant": false,
25
+ "llm_int8_enable_fp32_cpu_offload": false,
26
+ "llm_int8_has_fp16_weight": false,
27
+ "llm_int8_skip_modules": null,
28
+ "llm_int8_threshold": 6.0,
29
+ "load_in_4bit": false,
30
+ "load_in_8bit": true,
31
+ "quant_method": "bitsandbytes"
32
+ },
33
+ "rms_norm_eps": 1e-06,
34
+ "rope_theta": 1000000.0,
35
+ "sliding_window": 32768,
36
+ "tie_word_embeddings": true,
37
+ "torch_dtype": "bfloat16",
38
+ "transformers_version": "4.40.0.dev0",
39
+ "use_cache": false,
40
+ "use_sliding_window": false,
41
+ "vocab_size": 151936
42
+ }
merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
runs/Apr11_16-32-20_volko-MS-7D09/events.out.tfevents.1712845940.volko-MS-7D09.38265.0 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a85576b4937d02bc9999cc71ce248f5820388874be11c945cb9a8dc1ffddc10f
3
+ size 107131
runs/Apr11_16-53-26_volko-MS-7D09/events.out.tfevents.1712847206.volko-MS-7D09.40309.0 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:580c7dbd47b1cfe881cdd965f46548671d6de873ddd41d8be7d4c4118cb844a0
3
+ size 107130
runs/Apr11_17-04-13_volko-MS-7D09/events.out.tfevents.1712847853.volko-MS-7D09.41247.0 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:17e8e4539db8c7bc2a450a68061192458958f1046af43c643afc7cba5e69addf
3
+ size 2772065
special_tokens_map.json ADDED
@@ -0,0 +1,20 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "additional_special_tokens": [
3
+ "<|im_start|>",
4
+ "<|im_end|>"
5
+ ],
6
+ "eos_token": {
7
+ "content": "<|endoftext|>",
8
+ "lstrip": false,
9
+ "normalized": false,
10
+ "rstrip": false,
11
+ "single_word": false
12
+ },
13
+ "pad_token": {
14
+ "content": "<|endoftext|>",
15
+ "lstrip": false,
16
+ "normalized": false,
17
+ "rstrip": false,
18
+ "single_word": false
19
+ }
20
+ }
tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
tokenizer_config.json ADDED
@@ -0,0 +1,43 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_prefix_space": false,
3
+ "added_tokens_decoder": {
4
+ "151643": {
5
+ "content": "<|endoftext|>",
6
+ "lstrip": false,
7
+ "normalized": false,
8
+ "rstrip": false,
9
+ "single_word": false,
10
+ "special": true
11
+ },
12
+ "151644": {
13
+ "content": "<|im_start|>",
14
+ "lstrip": false,
15
+ "normalized": false,
16
+ "rstrip": false,
17
+ "single_word": false,
18
+ "special": true
19
+ },
20
+ "151645": {
21
+ "content": "<|im_end|>",
22
+ "lstrip": false,
23
+ "normalized": false,
24
+ "rstrip": false,
25
+ "single_word": false,
26
+ "special": true
27
+ }
28
+ },
29
+ "additional_special_tokens": [
30
+ "<|im_start|>",
31
+ "<|im_end|>"
32
+ ],
33
+ "bos_token": null,
34
+ "chat_template": "{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system\nYou are a helpful assistant<|im_end|>\n' }}{% endif %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
35
+ "clean_up_tokenization_spaces": false,
36
+ "eos_token": "<|endoftext|>",
37
+ "errors": "replace",
38
+ "model_max_length": 32768,
39
+ "pad_token": "<|endoftext|>",
40
+ "split_special_tokens": false,
41
+ "tokenizer_class": "Qwen2Tokenizer",
42
+ "unk_token": null
43
+ }
vocab.json ADDED
The diff for this file is too large to render. See raw diff