leo009 commited on
Commit
df586a8
1 Parent(s): d9e51e9

Upload folder using huggingface_hub

Browse files
This view is limited to 50 files because it contains too many changes.   See raw diff
Files changed (50) hide show
  1. README.md +141 -0
  2. adapter_config.json +34 -0
  3. adapter_model.bin +3 -0
  4. added_tokens.json +5 -0
  5. checkpoint-1272/README.md +202 -0
  6. checkpoint-1272/adapter_config.json +34 -0
  7. checkpoint-1272/adapter_model.safetensors +3 -0
  8. checkpoint-1272/added_tokens.json +5 -0
  9. checkpoint-1272/merges.txt +0 -0
  10. checkpoint-1272/optimizer.pt +3 -0
  11. checkpoint-1272/rng_state.pth +3 -0
  12. checkpoint-1272/scheduler.pt +3 -0
  13. checkpoint-1272/special_tokens_map.json +20 -0
  14. checkpoint-1272/tokenizer.json +0 -0
  15. checkpoint-1272/tokenizer_config.json +43 -0
  16. checkpoint-1272/trainer_state.json +0 -0
  17. checkpoint-1272/training_args.bin +3 -0
  18. checkpoint-1272/vocab.json +0 -0
  19. checkpoint-318/README.md +202 -0
  20. checkpoint-318/adapter_config.json +34 -0
  21. checkpoint-318/adapter_model.safetensors +3 -0
  22. checkpoint-318/added_tokens.json +5 -0
  23. checkpoint-318/merges.txt +0 -0
  24. checkpoint-318/optimizer.pt +3 -0
  25. checkpoint-318/rng_state.pth +3 -0
  26. checkpoint-318/scheduler.pt +3 -0
  27. checkpoint-318/special_tokens_map.json +20 -0
  28. checkpoint-318/tokenizer.json +0 -0
  29. checkpoint-318/tokenizer_config.json +43 -0
  30. checkpoint-318/trainer_state.json +2291 -0
  31. checkpoint-318/training_args.bin +3 -0
  32. checkpoint-318/vocab.json +0 -0
  33. checkpoint-636/README.md +202 -0
  34. checkpoint-636/adapter_config.json +34 -0
  35. checkpoint-636/adapter_model.safetensors +3 -0
  36. checkpoint-636/added_tokens.json +5 -0
  37. checkpoint-636/merges.txt +0 -0
  38. checkpoint-636/optimizer.pt +3 -0
  39. checkpoint-636/rng_state.pth +3 -0
  40. checkpoint-636/scheduler.pt +3 -0
  41. checkpoint-636/special_tokens_map.json +20 -0
  42. checkpoint-636/tokenizer.json +0 -0
  43. checkpoint-636/tokenizer_config.json +43 -0
  44. checkpoint-636/trainer_state.json +0 -0
  45. checkpoint-636/training_args.bin +3 -0
  46. checkpoint-636/vocab.json +0 -0
  47. checkpoint-954/README.md +202 -0
  48. checkpoint-954/adapter_config.json +34 -0
  49. checkpoint-954/adapter_model.safetensors +3 -0
  50. checkpoint-954/added_tokens.json +5 -0
README.md ADDED
@@ -0,0 +1,141 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ library_name: peft
4
+ tags:
5
+ - generated_from_trainer
6
+ base_model: Qwen/Qwen2-7B
7
+ model-index:
8
+ - name: outputs/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: `0.4.1`
19
+ ```yaml
20
+ base_model: Qwen/Qwen2-7B
21
+ trust_remote_code: true
22
+ load_in_8bit: false
23
+ load_in_4bit: true
24
+ strict: false
25
+ datasets:
26
+ - path: tatsu-lab/alpaca
27
+ type: alpaca
28
+ dataset_prepared_path:
29
+ val_set_size: 0.05
30
+ output_dir: ./outputs/out
31
+ sequence_len: 2048
32
+ sample_packing: true
33
+ eval_sample_packing: true
34
+ pad_to_sequence_len: true
35
+ adapter: qlora
36
+ lora_model_dir:
37
+ lora_r: 32
38
+ lora_alpha: 64
39
+ lora_dropout: 0.05
40
+ lora_target_linear: true
41
+ lora_fan_in_fan_out:
42
+ wandb_project:
43
+ wandb_entity:
44
+ wandb_watch:
45
+ wandb_name:
46
+ wandb_log_model:
47
+ gradient_accumulation_steps: 8
48
+ micro_batch_size: 1
49
+ num_epochs: 4
50
+ optimizer: adamw_torch
51
+ lr_scheduler: cosine
52
+ learning_rate: 0.0002
53
+ train_on_inputs: false
54
+ group_by_length: false
55
+ bf16: auto
56
+ fp16:
57
+ tf32: true
58
+ gradient_checkpointing: false
59
+ gradient_checkpointing_kwargs:
60
+ use_reentrant: false
61
+ early_stopping_patience:
62
+ resume_from_checkpoint:
63
+ local_rank:
64
+ logging_steps: 1
65
+ xformers_attention:
66
+ flash_attention: false
67
+ warmup_steps: 10
68
+ evals_per_epoch: 4
69
+ saves_per_epoch: 1
70
+ debug:
71
+ deepspeed:
72
+ weight_decay: 0.0
73
+ special_tokens:
74
+
75
+ ```
76
+
77
+ </details><br>
78
+
79
+ # outputs/out
80
+
81
+ This model is a fine-tuned version of [Qwen/Qwen2-7B](https://huggingface.co/Qwen/Qwen2-7B) on the None dataset.
82
+ It achieves the following results on the evaluation set:
83
+ - Loss: 4.3265
84
+
85
+ ## Model description
86
+
87
+ More information needed
88
+
89
+ ## Intended uses & limitations
90
+
91
+ More information needed
92
+
93
+ ## Training and evaluation data
94
+
95
+ More information needed
96
+
97
+ ## Training procedure
98
+
99
+ ### Training hyperparameters
100
+
101
+ The following hyperparameters were used during training:
102
+ - learning_rate: 0.0002
103
+ - train_batch_size: 1
104
+ - eval_batch_size: 1
105
+ - seed: 42
106
+ - gradient_accumulation_steps: 8
107
+ - total_train_batch_size: 8
108
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
109
+ - lr_scheduler_type: cosine
110
+ - lr_scheduler_warmup_steps: 10
111
+ - num_epochs: 4
112
+
113
+ ### Training results
114
+
115
+ | Training Loss | Epoch | Step | Validation Loss |
116
+ |:-------------:|:------:|:----:|:---------------:|
117
+ | 10.7953 | 0.0031 | 1 | 10.8104 |
118
+ | 5.4963 | 0.2513 | 80 | 5.4101 |
119
+ | 5.0323 | 0.5026 | 160 | 5.0758 |
120
+ | 4.9877 | 0.7538 | 240 | 4.8417 |
121
+ | 4.7408 | 1.0051 | 320 | 4.6180 |
122
+ | 4.5097 | 1.2442 | 400 | 4.5066 |
123
+ | 4.3959 | 1.4955 | 480 | 4.4513 |
124
+ | 4.2488 | 1.7468 | 560 | 4.4107 |
125
+ | 4.3507 | 1.9980 | 640 | 4.3784 |
126
+ | 4.2352 | 2.2352 | 720 | 4.3684 |
127
+ | 4.2141 | 2.4865 | 800 | 4.3505 |
128
+ | 4.2739 | 2.7377 | 880 | 4.3375 |
129
+ | 4.4037 | 2.9890 | 960 | 4.3310 |
130
+ | 4.195 | 3.2269 | 1040 | 4.3287 |
131
+ | 4.1996 | 3.4782 | 1120 | 4.3268 |
132
+ | 4.1353 | 3.7295 | 1200 | 4.3265 |
133
+
134
+
135
+ ### Framework versions
136
+
137
+ - PEFT 0.11.1
138
+ - Transformers 4.41.1
139
+ - Pytorch 2.1.2+cu118
140
+ - Datasets 2.19.1
141
+ - Tokenizers 0.19.1
adapter_config.json ADDED
@@ -0,0 +1,34 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "Qwen/Qwen2-7B",
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": 64,
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
+ "q_proj",
24
+ "v_proj",
25
+ "k_proj",
26
+ "down_proj",
27
+ "gate_proj",
28
+ "o_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 sha256:8182fe0f09118e42ee24f7be2305434cd9ed061a857d5649f849c4e2e9cda598
3
+ size 161622314
added_tokens.json ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+ {
2
+ "<|endoftext|>": 151643,
3
+ "<|im_end|>": 151645,
4
+ "<|im_start|>": 151644
5
+ }
checkpoint-1272/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ base_model: Qwen/Qwen2-7B
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 0.11.1
checkpoint-1272/adapter_config.json ADDED
@@ -0,0 +1,34 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "Qwen/Qwen2-7B",
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": 64,
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
+ "q_proj",
24
+ "v_proj",
25
+ "k_proj",
26
+ "down_proj",
27
+ "gate_proj",
28
+ "o_proj",
29
+ "up_proj"
30
+ ],
31
+ "task_type": "CAUSAL_LM",
32
+ "use_dora": false,
33
+ "use_rslora": false
34
+ }
checkpoint-1272/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:16a20e60e858d2682abc14528a71fccccf14339ac8667eeacbeb2091b6f76bd5
3
+ size 161533584
checkpoint-1272/added_tokens.json ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+ {
2
+ "<|endoftext|>": 151643,
3
+ "<|im_end|>": 151645,
4
+ "<|im_start|>": 151644
5
+ }
checkpoint-1272/merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-1272/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6719c69de9c12cb87233d422b5d745ae6a388fd8edc923389d893c2aeb4b4813
3
+ size 323292010
checkpoint-1272/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a4a6fd22b5a4ce5f800a83b8932a9fe2576ea0ffe9b9beff333869bfd7b6cf2c
3
+ size 14244
checkpoint-1272/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1b5a8f3dd119b7d57929465357243f6d4aae3de0ec76a858fb5197d358a60f4c
3
+ size 1064
checkpoint-1272/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-1272/tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-1272/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-1272/trainer_state.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-1272/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:34c048912f6ba3fdf50f66b1635aa253feb31cfba85c9f47fc5603099baef225
3
+ size 5944
checkpoint-1272/vocab.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-318/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ base_model: Qwen/Qwen2-7B
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 0.11.1
checkpoint-318/adapter_config.json ADDED
@@ -0,0 +1,34 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "Qwen/Qwen2-7B",
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": 64,
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
+ "q_proj",
24
+ "v_proj",
25
+ "k_proj",
26
+ "down_proj",
27
+ "gate_proj",
28
+ "o_proj",
29
+ "up_proj"
30
+ ],
31
+ "task_type": "CAUSAL_LM",
32
+ "use_dora": false,
33
+ "use_rslora": false
34
+ }
checkpoint-318/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f56d15074efcbd4884547275ec291a7576da3bf3c9e0b0c1fbd56f6835d3dd17
3
+ size 161533584
checkpoint-318/added_tokens.json ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+ {
2
+ "<|endoftext|>": 151643,
3
+ "<|im_end|>": 151645,
4
+ "<|im_start|>": 151644
5
+ }
checkpoint-318/merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-318/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:73bbb72cb3285a1d5b4aadfbc9bfa173b41e3770dca4d49265bf67c923a69c59
3
+ size 323292010
checkpoint-318/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:767e13f11ef09bcfb4e0e134c72ea653c7855060e44fb6dcb5ccff5902c50afb
3
+ size 14244
checkpoint-318/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:4ff5efa8ad7dad6adb047949e33858535b3068c546845d66e19365128712ead9
3
+ size 1064
checkpoint-318/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-318/tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-318/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-318/trainer_state.json ADDED
@@ -0,0 +1,2291 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": null,
3
+ "best_model_checkpoint": null,
4
+ "epoch": 0.9988221436984688,
5
+ "eval_steps": 80,
6
+ "global_step": 318,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.0031409501374165686,
13
+ "grad_norm": 5.125,
14
+ "learning_rate": 2e-05,
15
+ "loss": 10.7953,
16
+ "step": 1
17
+ },
18
+ {
19
+ "epoch": 0.0031409501374165686,
20
+ "eval_loss": 10.810359001159668,
21
+ "eval_runtime": 65.1601,
22
+ "eval_samples_per_second": 39.917,
23
+ "eval_steps_per_second": 39.917,
24
+ "step": 1
25
+ },
26
+ {
27
+ "epoch": 0.006281900274833137,
28
+ "grad_norm": 4.59375,
29
+ "learning_rate": 4e-05,
30
+ "loss": 10.599,
31
+ "step": 2
32
+ },
33
+ {
34
+ "epoch": 0.009422850412249705,
35
+ "grad_norm": 5.65625,
36
+ "learning_rate": 6e-05,
37
+ "loss": 10.8341,
38
+ "step": 3
39
+ },
40
+ {
41
+ "epoch": 0.012563800549666274,
42
+ "grad_norm": 4.59375,
43
+ "learning_rate": 8e-05,
44
+ "loss": 10.2321,
45
+ "step": 4
46
+ },
47
+ {
48
+ "epoch": 0.015704750687082842,
49
+ "grad_norm": 5.09375,
50
+ "learning_rate": 0.0001,
51
+ "loss": 9.926,
52
+ "step": 5
53
+ },
54
+ {
55
+ "epoch": 0.01884570082449941,
56
+ "grad_norm": 5.09375,
57
+ "learning_rate": 0.00012,
58
+ "loss": 9.2807,
59
+ "step": 6
60
+ },
61
+ {
62
+ "epoch": 0.02198665096191598,
63
+ "grad_norm": 5.21875,
64
+ "learning_rate": 0.00014,
65
+ "loss": 8.7401,
66
+ "step": 7
67
+ },
68
+ {
69
+ "epoch": 0.02512760109933255,
70
+ "grad_norm": 5.3125,
71
+ "learning_rate": 0.00016,
72
+ "loss": 7.7479,
73
+ "step": 8
74
+ },
75
+ {
76
+ "epoch": 0.028268551236749116,
77
+ "grad_norm": 3.78125,
78
+ "learning_rate": 0.00018,
79
+ "loss": 7.3356,
80
+ "step": 9
81
+ },
82
+ {
83
+ "epoch": 0.031409501374165684,
84
+ "grad_norm": 4.15625,
85
+ "learning_rate": 0.0002,
86
+ "loss": 6.8649,
87
+ "step": 10
88
+ },
89
+ {
90
+ "epoch": 0.03455045151158225,
91
+ "grad_norm": 1.9296875,
92
+ "learning_rate": 0.00019999969015048862,
93
+ "loss": 6.7994,
94
+ "step": 11
95
+ },
96
+ {
97
+ "epoch": 0.03769140164899882,
98
+ "grad_norm": 1.2265625,
99
+ "learning_rate": 0.0001999987606038746,
100
+ "loss": 6.2436,
101
+ "step": 12
102
+ },
103
+ {
104
+ "epoch": 0.040832351786415394,
105
+ "grad_norm": 2.125,
106
+ "learning_rate": 0.0001999972113659183,
107
+ "loss": 6.6684,
108
+ "step": 13
109
+ },
110
+ {
111
+ "epoch": 0.04397330192383196,
112
+ "grad_norm": 0.9921875,
113
+ "learning_rate": 0.00019999504244622043,
114
+ "loss": 6.4968,
115
+ "step": 14
116
+ },
117
+ {
118
+ "epoch": 0.04711425206124853,
119
+ "grad_norm": 1.0625,
120
+ "learning_rate": 0.00019999225385822165,
121
+ "loss": 6.3331,
122
+ "step": 15
123
+ },
124
+ {
125
+ "epoch": 0.0502552021986651,
126
+ "grad_norm": 0.88671875,
127
+ "learning_rate": 0.00019998884561920284,
128
+ "loss": 6.3441,
129
+ "step": 16
130
+ },
131
+ {
132
+ "epoch": 0.053396152336081665,
133
+ "grad_norm": 1.171875,
134
+ "learning_rate": 0.00019998481775028491,
135
+ "loss": 5.8419,
136
+ "step": 17
137
+ },
138
+ {
139
+ "epoch": 0.05653710247349823,
140
+ "grad_norm": 1.3203125,
141
+ "learning_rate": 0.0001999801702764284,
142
+ "loss": 6.1942,
143
+ "step": 18
144
+ },
145
+ {
146
+ "epoch": 0.0596780526109148,
147
+ "grad_norm": 1.75,
148
+ "learning_rate": 0.00019997490322643376,
149
+ "loss": 6.017,
150
+ "step": 19
151
+ },
152
+ {
153
+ "epoch": 0.06281900274833137,
154
+ "grad_norm": 1.1875,
155
+ "learning_rate": 0.00019996901663294078,
156
+ "loss": 6.2501,
157
+ "step": 20
158
+ },
159
+ {
160
+ "epoch": 0.06595995288574794,
161
+ "grad_norm": 0.9296875,
162
+ "learning_rate": 0.00019996251053242865,
163
+ "loss": 5.9597,
164
+ "step": 21
165
+ },
166
+ {
167
+ "epoch": 0.0691009030231645,
168
+ "grad_norm": 1.8984375,
169
+ "learning_rate": 0.0001999553849652156,
170
+ "loss": 6.0591,
171
+ "step": 22
172
+ },
173
+ {
174
+ "epoch": 0.07224185316058107,
175
+ "grad_norm": 1.265625,
176
+ "learning_rate": 0.00019994763997545874,
177
+ "loss": 6.2802,
178
+ "step": 23
179
+ },
180
+ {
181
+ "epoch": 0.07538280329799764,
182
+ "grad_norm": 1.7265625,
183
+ "learning_rate": 0.00019993927561115366,
184
+ "loss": 6.082,
185
+ "step": 24
186
+ },
187
+ {
188
+ "epoch": 0.0785237534354142,
189
+ "grad_norm": 1.0,
190
+ "learning_rate": 0.00019993029192413424,
191
+ "loss": 6.1596,
192
+ "step": 25
193
+ },
194
+ {
195
+ "epoch": 0.08166470357283079,
196
+ "grad_norm": 1.609375,
197
+ "learning_rate": 0.00019992068897007232,
198
+ "loss": 5.9254,
199
+ "step": 26
200
+ },
201
+ {
202
+ "epoch": 0.08480565371024736,
203
+ "grad_norm": 1.5234375,
204
+ "learning_rate": 0.0001999104668084773,
205
+ "loss": 5.893,
206
+ "step": 27
207
+ },
208
+ {
209
+ "epoch": 0.08794660384766392,
210
+ "grad_norm": 0.90234375,
211
+ "learning_rate": 0.00019989962550269583,
212
+ "loss": 6.1184,
213
+ "step": 28
214
+ },
215
+ {
216
+ "epoch": 0.09108755398508049,
217
+ "grad_norm": 0.88671875,
218
+ "learning_rate": 0.00019988816511991135,
219
+ "loss": 5.9582,
220
+ "step": 29
221
+ },
222
+ {
223
+ "epoch": 0.09422850412249706,
224
+ "grad_norm": 1.0078125,
225
+ "learning_rate": 0.00019987608573114376,
226
+ "loss": 5.8845,
227
+ "step": 30
228
+ },
229
+ {
230
+ "epoch": 0.09736945425991363,
231
+ "grad_norm": 1.3046875,
232
+ "learning_rate": 0.0001998633874112489,
233
+ "loss": 6.1202,
234
+ "step": 31
235
+ },
236
+ {
237
+ "epoch": 0.1005104043973302,
238
+ "grad_norm": 1.1015625,
239
+ "learning_rate": 0.00019985007023891815,
240
+ "loss": 5.7627,
241
+ "step": 32
242
+ },
243
+ {
244
+ "epoch": 0.10365135453474676,
245
+ "grad_norm": 0.8828125,
246
+ "learning_rate": 0.00019983613429667792,
247
+ "loss": 6.0619,
248
+ "step": 33
249
+ },
250
+ {
251
+ "epoch": 0.10679230467216333,
252
+ "grad_norm": 1.0078125,
253
+ "learning_rate": 0.00019982157967088904,
254
+ "loss": 5.683,
255
+ "step": 34
256
+ },
257
+ {
258
+ "epoch": 0.1099332548095799,
259
+ "grad_norm": 1.1640625,
260
+ "learning_rate": 0.0001998064064517464,
261
+ "loss": 5.8008,
262
+ "step": 35
263
+ },
264
+ {
265
+ "epoch": 0.11307420494699646,
266
+ "grad_norm": 1.375,
267
+ "learning_rate": 0.00019979061473327837,
268
+ "loss": 5.8867,
269
+ "step": 36
270
+ },
271
+ {
272
+ "epoch": 0.11621515508441303,
273
+ "grad_norm": 1.671875,
274
+ "learning_rate": 0.000199774204613346,
275
+ "loss": 5.9331,
276
+ "step": 37
277
+ },
278
+ {
279
+ "epoch": 0.1193561052218296,
280
+ "grad_norm": 1.4375,
281
+ "learning_rate": 0.00019975717619364263,
282
+ "loss": 5.4695,
283
+ "step": 38
284
+ },
285
+ {
286
+ "epoch": 0.12249705535924617,
287
+ "grad_norm": 1.4765625,
288
+ "learning_rate": 0.0001997395295796933,
289
+ "loss": 5.9711,
290
+ "step": 39
291
+ },
292
+ {
293
+ "epoch": 0.12563800549666274,
294
+ "grad_norm": 1.2421875,
295
+ "learning_rate": 0.00019972126488085378,
296
+ "loss": 5.7401,
297
+ "step": 40
298
+ },
299
+ {
300
+ "epoch": 0.12877895563407932,
301
+ "grad_norm": 1.390625,
302
+ "learning_rate": 0.00019970238221031034,
303
+ "loss": 5.7064,
304
+ "step": 41
305
+ },
306
+ {
307
+ "epoch": 0.13191990577149587,
308
+ "grad_norm": 1.3046875,
309
+ "learning_rate": 0.00019968288168507864,
310
+ "loss": 5.6272,
311
+ "step": 42
312
+ },
313
+ {
314
+ "epoch": 0.13506085590891245,
315
+ "grad_norm": 1.8359375,
316
+ "learning_rate": 0.00019966276342600327,
317
+ "loss": 5.4439,
318
+ "step": 43
319
+ },
320
+ {
321
+ "epoch": 0.138201806046329,
322
+ "grad_norm": 1.265625,
323
+ "learning_rate": 0.0001996420275577569,
324
+ "loss": 5.9631,
325
+ "step": 44
326
+ },
327
+ {
328
+ "epoch": 0.1413427561837456,
329
+ "grad_norm": 1.6796875,
330
+ "learning_rate": 0.00019962067420883944,
331
+ "loss": 5.8393,
332
+ "step": 45
333
+ },
334
+ {
335
+ "epoch": 0.14448370632116214,
336
+ "grad_norm": 1.53125,
337
+ "learning_rate": 0.00019959870351157747,
338
+ "loss": 5.7997,
339
+ "step": 46
340
+ },
341
+ {
342
+ "epoch": 0.14762465645857872,
343
+ "grad_norm": 1.3984375,
344
+ "learning_rate": 0.0001995761156021231,
345
+ "loss": 5.656,
346
+ "step": 47
347
+ },
348
+ {
349
+ "epoch": 0.15076560659599528,
350
+ "grad_norm": 1.4921875,
351
+ "learning_rate": 0.00019955291062045345,
352
+ "loss": 5.7152,
353
+ "step": 48
354
+ },
355
+ {
356
+ "epoch": 0.15390655673341186,
357
+ "grad_norm": 1.828125,
358
+ "learning_rate": 0.00019952908871036956,
359
+ "loss": 5.7215,
360
+ "step": 49
361
+ },
362
+ {
363
+ "epoch": 0.1570475068708284,
364
+ "grad_norm": 1.0,
365
+ "learning_rate": 0.0001995046500194955,
366
+ "loss": 5.6857,
367
+ "step": 50
368
+ },
369
+ {
370
+ "epoch": 0.160188457008245,
371
+ "grad_norm": 1.3984375,
372
+ "learning_rate": 0.00019947959469927772,
373
+ "loss": 5.6698,
374
+ "step": 51
375
+ },
376
+ {
377
+ "epoch": 0.16332940714566158,
378
+ "grad_norm": 1.3515625,
379
+ "learning_rate": 0.0001994539229049837,
380
+ "loss": 5.2906,
381
+ "step": 52
382
+ },
383
+ {
384
+ "epoch": 0.16647035728307813,
385
+ "grad_norm": 1.25,
386
+ "learning_rate": 0.00019942763479570132,
387
+ "loss": 5.4673,
388
+ "step": 53
389
+ },
390
+ {
391
+ "epoch": 0.1696113074204947,
392
+ "grad_norm": 0.890625,
393
+ "learning_rate": 0.00019940073053433777,
394
+ "loss": 5.5959,
395
+ "step": 54
396
+ },
397
+ {
398
+ "epoch": 0.17275225755791127,
399
+ "grad_norm": 1.59375,
400
+ "learning_rate": 0.00019937321028761846,
401
+ "loss": 5.9431,
402
+ "step": 55
403
+ },
404
+ {
405
+ "epoch": 0.17589320769532785,
406
+ "grad_norm": 1.59375,
407
+ "learning_rate": 0.00019934507422608608,
408
+ "loss": 5.754,
409
+ "step": 56
410
+ },
411
+ {
412
+ "epoch": 0.1790341578327444,
413
+ "grad_norm": 0.984375,
414
+ "learning_rate": 0.00019931632252409955,
415
+ "loss": 5.405,
416
+ "step": 57
417
+ },
418
+ {
419
+ "epoch": 0.18217510797016098,
420
+ "grad_norm": 1.03125,
421
+ "learning_rate": 0.00019928695535983287,
422
+ "loss": 5.5907,
423
+ "step": 58
424
+ },
425
+ {
426
+ "epoch": 0.18531605810757754,
427
+ "grad_norm": 1.2265625,
428
+ "learning_rate": 0.00019925697291527415,
429
+ "loss": 5.7941,
430
+ "step": 59
431
+ },
432
+ {
433
+ "epoch": 0.18845700824499412,
434
+ "grad_norm": 1.0078125,
435
+ "learning_rate": 0.00019922637537622418,
436
+ "loss": 5.6169,
437
+ "step": 60
438
+ },
439
+ {
440
+ "epoch": 0.19159795838241067,
441
+ "grad_norm": 1.5,
442
+ "learning_rate": 0.00019919516293229569,
443
+ "loss": 5.5379,
444
+ "step": 61
445
+ },
446
+ {
447
+ "epoch": 0.19473890851982725,
448
+ "grad_norm": 0.8203125,
449
+ "learning_rate": 0.00019916333577691184,
450
+ "loss": 5.6157,
451
+ "step": 62
452
+ },
453
+ {
454
+ "epoch": 0.1978798586572438,
455
+ "grad_norm": 1.484375,
456
+ "learning_rate": 0.00019913089410730526,
457
+ "loss": 5.5043,
458
+ "step": 63
459
+ },
460
+ {
461
+ "epoch": 0.2010208087946604,
462
+ "grad_norm": 0.98046875,
463
+ "learning_rate": 0.00019909783812451664,
464
+ "loss": 5.7083,
465
+ "step": 64
466
+ },
467
+ {
468
+ "epoch": 0.20416175893207694,
469
+ "grad_norm": 1.125,
470
+ "learning_rate": 0.00019906416803339353,
471
+ "loss": 5.5739,
472
+ "step": 65
473
+ },
474
+ {
475
+ "epoch": 0.20730270906949352,
476
+ "grad_norm": 1.375,
477
+ "learning_rate": 0.00019902988404258922,
478
+ "loss": 5.5447,
479
+ "step": 66
480
+ },
481
+ {
482
+ "epoch": 0.21044365920691008,
483
+ "grad_norm": 1.2109375,
484
+ "learning_rate": 0.00019899498636456126,
485
+ "loss": 5.3392,
486
+ "step": 67
487
+ },
488
+ {
489
+ "epoch": 0.21358460934432666,
490
+ "grad_norm": 1.1171875,
491
+ "learning_rate": 0.0001989594752155702,
492
+ "loss": 5.3176,
493
+ "step": 68
494
+ },
495
+ {
496
+ "epoch": 0.21672555948174324,
497
+ "grad_norm": 0.93359375,
498
+ "learning_rate": 0.00019892335081567826,
499
+ "loss": 5.1688,
500
+ "step": 69
501
+ },
502
+ {
503
+ "epoch": 0.2198665096191598,
504
+ "grad_norm": 0.953125,
505
+ "learning_rate": 0.00019888661338874803,
506
+ "loss": 5.5142,
507
+ "step": 70
508
+ },
509
+ {
510
+ "epoch": 0.22300745975657638,
511
+ "grad_norm": 1.1484375,
512
+ "learning_rate": 0.000198849263162441,
513
+ "loss": 5.3004,
514
+ "step": 71
515
+ },
516
+ {
517
+ "epoch": 0.22614840989399293,
518
+ "grad_norm": 0.7890625,
519
+ "learning_rate": 0.0001988113003682161,
520
+ "loss": 5.5914,
521
+ "step": 72
522
+ },
523
+ {
524
+ "epoch": 0.2292893600314095,
525
+ "grad_norm": 0.71484375,
526
+ "learning_rate": 0.00019877272524132847,
527
+ "loss": 5.4175,
528
+ "step": 73
529
+ },
530
+ {
531
+ "epoch": 0.23243031016882607,
532
+ "grad_norm": 0.99609375,
533
+ "learning_rate": 0.00019873353802082771,
534
+ "loss": 5.0854,
535
+ "step": 74
536
+ },
537
+ {
538
+ "epoch": 0.23557126030624265,
539
+ "grad_norm": 1.046875,
540
+ "learning_rate": 0.00019869373894955669,
541
+ "loss": 5.5772,
542
+ "step": 75
543
+ },
544
+ {
545
+ "epoch": 0.2387122104436592,
546
+ "grad_norm": 1.390625,
547
+ "learning_rate": 0.00019865332827414988,
548
+ "loss": 5.4289,
549
+ "step": 76
550
+ },
551
+ {
552
+ "epoch": 0.24185316058107578,
553
+ "grad_norm": 1.3203125,
554
+ "learning_rate": 0.0001986123062450318,
555
+ "loss": 5.5427,
556
+ "step": 77
557
+ },
558
+ {
559
+ "epoch": 0.24499411071849234,
560
+ "grad_norm": 0.82421875,
561
+ "learning_rate": 0.0001985706731164156,
562
+ "loss": 5.3294,
563
+ "step": 78
564
+ },
565
+ {
566
+ "epoch": 0.24813506085590892,
567
+ "grad_norm": 1.4921875,
568
+ "learning_rate": 0.00019852842914630137,
569
+ "loss": 5.3756,
570
+ "step": 79
571
+ },
572
+ {
573
+ "epoch": 0.25127601099332547,
574
+ "grad_norm": 1.375,
575
+ "learning_rate": 0.00019848557459647455,
576
+ "loss": 5.4963,
577
+ "step": 80
578
+ },
579
+ {
580
+ "epoch": 0.25127601099332547,
581
+ "eval_loss": 5.410098075866699,
582
+ "eval_runtime": 66.9514,
583
+ "eval_samples_per_second": 38.849,
584
+ "eval_steps_per_second": 38.849,
585
+ "step": 80
586
+ },
587
+ {
588
+ "epoch": 0.254416961130742,
589
+ "grad_norm": 1.0703125,
590
+ "learning_rate": 0.00019844210973250437,
591
+ "loss": 5.4053,
592
+ "step": 81
593
+ },
594
+ {
595
+ "epoch": 0.25755791126815863,
596
+ "grad_norm": 1.3359375,
597
+ "learning_rate": 0.0001983980348237422,
598
+ "loss": 5.3084,
599
+ "step": 82
600
+ },
601
+ {
602
+ "epoch": 0.2606988614055752,
603
+ "grad_norm": 0.95703125,
604
+ "learning_rate": 0.00019835335014331976,
605
+ "loss": 5.4774,
606
+ "step": 83
607
+ },
608
+ {
609
+ "epoch": 0.26383981154299174,
610
+ "grad_norm": 1.3046875,
611
+ "learning_rate": 0.00019830805596814766,
612
+ "loss": 5.3591,
613
+ "step": 84
614
+ },
615
+ {
616
+ "epoch": 0.2669807616804083,
617
+ "grad_norm": 1.46875,
618
+ "learning_rate": 0.00019826215257891342,
619
+ "loss": 5.2504,
620
+ "step": 85
621
+ },
622
+ {
623
+ "epoch": 0.2701217118178249,
624
+ "grad_norm": 1.1171875,
625
+ "learning_rate": 0.00019821564026007988,
626
+ "loss": 5.2333,
627
+ "step": 86
628
+ },
629
+ {
630
+ "epoch": 0.27326266195524146,
631
+ "grad_norm": 1.4765625,
632
+ "learning_rate": 0.0001981685192998834,
633
+ "loss": 5.4557,
634
+ "step": 87
635
+ },
636
+ {
637
+ "epoch": 0.276403612092658,
638
+ "grad_norm": 1.1171875,
639
+ "learning_rate": 0.00019812078999033222,
640
+ "loss": 5.5066,
641
+ "step": 88
642
+ },
643
+ {
644
+ "epoch": 0.2795445622300746,
645
+ "grad_norm": 1.0234375,
646
+ "learning_rate": 0.00019807245262720426,
647
+ "loss": 5.3617,
648
+ "step": 89
649
+ },
650
+ {
651
+ "epoch": 0.2826855123674912,
652
+ "grad_norm": 1.0234375,
653
+ "learning_rate": 0.0001980235075100458,
654
+ "loss": 5.4076,
655
+ "step": 90
656
+ },
657
+ {
658
+ "epoch": 0.28582646250490773,
659
+ "grad_norm": 0.921875,
660
+ "learning_rate": 0.00019797395494216923,
661
+ "loss": 5.2482,
662
+ "step": 91
663
+ },
664
+ {
665
+ "epoch": 0.2889674126423243,
666
+ "grad_norm": 1.1640625,
667
+ "learning_rate": 0.00019792379523065126,
668
+ "loss": 5.1448,
669
+ "step": 92
670
+ },
671
+ {
672
+ "epoch": 0.2921083627797409,
673
+ "grad_norm": 1.1015625,
674
+ "learning_rate": 0.0001978730286863312,
675
+ "loss": 5.2483,
676
+ "step": 93
677
+ },
678
+ {
679
+ "epoch": 0.29524931291715745,
680
+ "grad_norm": 1.0234375,
681
+ "learning_rate": 0.0001978216556238088,
682
+ "loss": 5.1698,
683
+ "step": 94
684
+ },
685
+ {
686
+ "epoch": 0.298390263054574,
687
+ "grad_norm": 0.91015625,
688
+ "learning_rate": 0.00019776967636144245,
689
+ "loss": 5.3225,
690
+ "step": 95
691
+ },
692
+ {
693
+ "epoch": 0.30153121319199055,
694
+ "grad_norm": 0.80859375,
695
+ "learning_rate": 0.00019771709122134713,
696
+ "loss": 5.3077,
697
+ "step": 96
698
+ },
699
+ {
700
+ "epoch": 0.30467216332940716,
701
+ "grad_norm": 0.76953125,
702
+ "learning_rate": 0.00019766390052939242,
703
+ "loss": 5.2636,
704
+ "step": 97
705
+ },
706
+ {
707
+ "epoch": 0.3078131134668237,
708
+ "grad_norm": 1.0390625,
709
+ "learning_rate": 0.00019761010461520054,
710
+ "loss": 5.4547,
711
+ "step": 98
712
+ },
713
+ {
714
+ "epoch": 0.31095406360424027,
715
+ "grad_norm": 0.85546875,
716
+ "learning_rate": 0.0001975557038121442,
717
+ "loss": 5.2564,
718
+ "step": 99
719
+ },
720
+ {
721
+ "epoch": 0.3140950137416568,
722
+ "grad_norm": 1.1484375,
723
+ "learning_rate": 0.00019750069845734473,
724
+ "loss": 4.9768,
725
+ "step": 100
726
+ },
727
+ {
728
+ "epoch": 0.31723596387907343,
729
+ "grad_norm": 1.0703125,
730
+ "learning_rate": 0.00019744508889166966,
731
+ "loss": 5.2283,
732
+ "step": 101
733
+ },
734
+ {
735
+ "epoch": 0.32037691401649,
736
+ "grad_norm": 1.34375,
737
+ "learning_rate": 0.00019738887545973102,
738
+ "loss": 5.4258,
739
+ "step": 102
740
+ },
741
+ {
742
+ "epoch": 0.32351786415390654,
743
+ "grad_norm": 1.2109375,
744
+ "learning_rate": 0.00019733205850988285,
745
+ "loss": 5.2331,
746
+ "step": 103
747
+ },
748
+ {
749
+ "epoch": 0.32665881429132315,
750
+ "grad_norm": 0.828125,
751
+ "learning_rate": 0.00019727463839421926,
752
+ "loss": 5.1852,
753
+ "step": 104
754
+ },
755
+ {
756
+ "epoch": 0.3297997644287397,
757
+ "grad_norm": 1.109375,
758
+ "learning_rate": 0.00019721661546857213,
759
+ "loss": 5.4063,
760
+ "step": 105
761
+ },
762
+ {
763
+ "epoch": 0.33294071456615626,
764
+ "grad_norm": 0.8359375,
765
+ "learning_rate": 0.000197157990092509,
766
+ "loss": 5.2671,
767
+ "step": 106
768
+ },
769
+ {
770
+ "epoch": 0.3360816647035728,
771
+ "grad_norm": 0.94140625,
772
+ "learning_rate": 0.00019709876262933066,
773
+ "loss": 5.3544,
774
+ "step": 107
775
+ },
776
+ {
777
+ "epoch": 0.3392226148409894,
778
+ "grad_norm": 0.9609375,
779
+ "learning_rate": 0.0001970389334460692,
780
+ "loss": 5.1728,
781
+ "step": 108
782
+ },
783
+ {
784
+ "epoch": 0.342363564978406,
785
+ "grad_norm": 0.921875,
786
+ "learning_rate": 0.00019697850291348548,
787
+ "loss": 5.3887,
788
+ "step": 109
789
+ },
790
+ {
791
+ "epoch": 0.34550451511582253,
792
+ "grad_norm": 0.8984375,
793
+ "learning_rate": 0.00019691747140606692,
794
+ "loss": 5.1095,
795
+ "step": 110
796
+ },
797
+ {
798
+ "epoch": 0.3486454652532391,
799
+ "grad_norm": 0.96875,
800
+ "learning_rate": 0.00019685583930202514,
801
+ "loss": 5.1703,
802
+ "step": 111
803
+ },
804
+ {
805
+ "epoch": 0.3517864153906557,
806
+ "grad_norm": 0.81640625,
807
+ "learning_rate": 0.0001967936069832937,
808
+ "loss": 5.17,
809
+ "step": 112
810
+ },
811
+ {
812
+ "epoch": 0.35492736552807225,
813
+ "grad_norm": 1.0625,
814
+ "learning_rate": 0.00019673077483552568,
815
+ "loss": 5.0519,
816
+ "step": 113
817
+ },
818
+ {
819
+ "epoch": 0.3580683156654888,
820
+ "grad_norm": 0.87109375,
821
+ "learning_rate": 0.00019666734324809125,
822
+ "loss": 5.186,
823
+ "step": 114
824
+ },
825
+ {
826
+ "epoch": 0.36120926580290535,
827
+ "grad_norm": 1.2578125,
828
+ "learning_rate": 0.00019660331261407544,
829
+ "loss": 5.0202,
830
+ "step": 115
831
+ },
832
+ {
833
+ "epoch": 0.36435021594032196,
834
+ "grad_norm": 0.70703125,
835
+ "learning_rate": 0.00019653868333027535,
836
+ "loss": 5.1102,
837
+ "step": 116
838
+ },
839
+ {
840
+ "epoch": 0.3674911660777385,
841
+ "grad_norm": 0.85546875,
842
+ "learning_rate": 0.00019647345579719807,
843
+ "loss": 5.1,
844
+ "step": 117
845
+ },
846
+ {
847
+ "epoch": 0.37063211621515507,
848
+ "grad_norm": 1.078125,
849
+ "learning_rate": 0.000196407630419058,
850
+ "loss": 5.0466,
851
+ "step": 118
852
+ },
853
+ {
854
+ "epoch": 0.3737730663525716,
855
+ "grad_norm": 1.1328125,
856
+ "learning_rate": 0.00019634120760377428,
857
+ "loss": 5.3088,
858
+ "step": 119
859
+ },
860
+ {
861
+ "epoch": 0.37691401648998824,
862
+ "grad_norm": 1.1796875,
863
+ "learning_rate": 0.00019627418776296858,
864
+ "loss": 5.2293,
865
+ "step": 120
866
+ },
867
+ {
868
+ "epoch": 0.3800549666274048,
869
+ "grad_norm": 1.1171875,
870
+ "learning_rate": 0.00019620657131196208,
871
+ "loss": 5.2738,
872
+ "step": 121
873
+ },
874
+ {
875
+ "epoch": 0.38319591676482134,
876
+ "grad_norm": 1.1171875,
877
+ "learning_rate": 0.00019613835866977335,
878
+ "loss": 4.9497,
879
+ "step": 122
880
+ },
881
+ {
882
+ "epoch": 0.38633686690223795,
883
+ "grad_norm": 0.9375,
884
+ "learning_rate": 0.00019606955025911542,
885
+ "loss": 5.2231,
886
+ "step": 123
887
+ },
888
+ {
889
+ "epoch": 0.3894778170396545,
890
+ "grad_norm": 0.93359375,
891
+ "learning_rate": 0.00019600014650639333,
892
+ "loss": 5.3426,
893
+ "step": 124
894
+ },
895
+ {
896
+ "epoch": 0.39261876717707106,
897
+ "grad_norm": 0.76953125,
898
+ "learning_rate": 0.00019593014784170153,
899
+ "loss": 5.0717,
900
+ "step": 125
901
+ },
902
+ {
903
+ "epoch": 0.3957597173144876,
904
+ "grad_norm": 0.9140625,
905
+ "learning_rate": 0.00019585955469882097,
906
+ "loss": 5.1569,
907
+ "step": 126
908
+ },
909
+ {
910
+ "epoch": 0.3989006674519042,
911
+ "grad_norm": 0.75390625,
912
+ "learning_rate": 0.0001957883675152167,
913
+ "loss": 4.9017,
914
+ "step": 127
915
+ },
916
+ {
917
+ "epoch": 0.4020416175893208,
918
+ "grad_norm": 0.96484375,
919
+ "learning_rate": 0.00019571658673203502,
920
+ "loss": 5.1124,
921
+ "step": 128
922
+ },
923
+ {
924
+ "epoch": 0.40518256772673733,
925
+ "grad_norm": 0.953125,
926
+ "learning_rate": 0.00019564421279410075,
927
+ "loss": 4.7849,
928
+ "step": 129
929
+ },
930
+ {
931
+ "epoch": 0.4083235178641539,
932
+ "grad_norm": 0.90234375,
933
+ "learning_rate": 0.00019557124614991443,
934
+ "loss": 5.1534,
935
+ "step": 130
936
+ },
937
+ {
938
+ "epoch": 0.4114644680015705,
939
+ "grad_norm": 1.015625,
940
+ "learning_rate": 0.00019549768725164967,
941
+ "loss": 5.2731,
942
+ "step": 131
943
+ },
944
+ {
945
+ "epoch": 0.41460541813898705,
946
+ "grad_norm": 1.0,
947
+ "learning_rate": 0.00019542353655515023,
948
+ "loss": 5.0467,
949
+ "step": 132
950
+ },
951
+ {
952
+ "epoch": 0.4177463682764036,
953
+ "grad_norm": 0.8671875,
954
+ "learning_rate": 0.00019534879451992728,
955
+ "loss": 4.8911,
956
+ "step": 133
957
+ },
958
+ {
959
+ "epoch": 0.42088731841382016,
960
+ "grad_norm": 0.875,
961
+ "learning_rate": 0.00019527346160915646,
962
+ "loss": 5.2338,
963
+ "step": 134
964
+ },
965
+ {
966
+ "epoch": 0.42402826855123676,
967
+ "grad_norm": 1.1171875,
968
+ "learning_rate": 0.00019519753828967508,
969
+ "loss": 5.1705,
970
+ "step": 135
971
+ },
972
+ {
973
+ "epoch": 0.4271692186886533,
974
+ "grad_norm": 0.96484375,
975
+ "learning_rate": 0.00019512102503197923,
976
+ "loss": 5.3178,
977
+ "step": 136
978
+ },
979
+ {
980
+ "epoch": 0.43031016882606987,
981
+ "grad_norm": 1.2734375,
982
+ "learning_rate": 0.00019504392231022076,
983
+ "loss": 5.1462,
984
+ "step": 137
985
+ },
986
+ {
987
+ "epoch": 0.4334511189634865,
988
+ "grad_norm": 1.0546875,
989
+ "learning_rate": 0.00019496623060220457,
990
+ "loss": 5.0293,
991
+ "step": 138
992
+ },
993
+ {
994
+ "epoch": 0.43659206910090304,
995
+ "grad_norm": 1.046875,
996
+ "learning_rate": 0.00019488795038938536,
997
+ "loss": 5.0523,
998
+ "step": 139
999
+ },
1000
+ {
1001
+ "epoch": 0.4397330192383196,
1002
+ "grad_norm": 1.7421875,
1003
+ "learning_rate": 0.00019480908215686486,
1004
+ "loss": 5.0893,
1005
+ "step": 140
1006
+ },
1007
+ {
1008
+ "epoch": 0.44287396937573614,
1009
+ "grad_norm": 0.79296875,
1010
+ "learning_rate": 0.00019472962639338875,
1011
+ "loss": 5.0682,
1012
+ "step": 141
1013
+ },
1014
+ {
1015
+ "epoch": 0.44601491951315275,
1016
+ "grad_norm": 1.265625,
1017
+ "learning_rate": 0.00019464958359134354,
1018
+ "loss": 5.1261,
1019
+ "step": 142
1020
+ },
1021
+ {
1022
+ "epoch": 0.4491558696505693,
1023
+ "grad_norm": 1.09375,
1024
+ "learning_rate": 0.00019456895424675382,
1025
+ "loss": 5.2513,
1026
+ "step": 143
1027
+ },
1028
+ {
1029
+ "epoch": 0.45229681978798586,
1030
+ "grad_norm": 0.87890625,
1031
+ "learning_rate": 0.00019448773885927877,
1032
+ "loss": 5.0248,
1033
+ "step": 144
1034
+ },
1035
+ {
1036
+ "epoch": 0.4554377699254024,
1037
+ "grad_norm": 1.1484375,
1038
+ "learning_rate": 0.00019440593793220936,
1039
+ "loss": 4.9527,
1040
+ "step": 145
1041
+ },
1042
+ {
1043
+ "epoch": 0.458578720062819,
1044
+ "grad_norm": 0.93359375,
1045
+ "learning_rate": 0.00019432355197246515,
1046
+ "loss": 5.1182,
1047
+ "step": 146
1048
+ },
1049
+ {
1050
+ "epoch": 0.4617196702002356,
1051
+ "grad_norm": 1.125,
1052
+ "learning_rate": 0.00019424058149059112,
1053
+ "loss": 5.043,
1054
+ "step": 147
1055
+ },
1056
+ {
1057
+ "epoch": 0.46486062033765213,
1058
+ "grad_norm": 0.98828125,
1059
+ "learning_rate": 0.00019415702700075453,
1060
+ "loss": 5.1351,
1061
+ "step": 148
1062
+ },
1063
+ {
1064
+ "epoch": 0.4680015704750687,
1065
+ "grad_norm": 1.234375,
1066
+ "learning_rate": 0.00019407288902074176,
1067
+ "loss": 5.0489,
1068
+ "step": 149
1069
+ },
1070
+ {
1071
+ "epoch": 0.4711425206124853,
1072
+ "grad_norm": 1.265625,
1073
+ "learning_rate": 0.00019398816807195498,
1074
+ "loss": 4.8494,
1075
+ "step": 150
1076
+ },
1077
+ {
1078
+ "epoch": 0.47428347074990185,
1079
+ "grad_norm": 0.9140625,
1080
+ "learning_rate": 0.00019390286467940918,
1081
+ "loss": 5.196,
1082
+ "step": 151
1083
+ },
1084
+ {
1085
+ "epoch": 0.4774244208873184,
1086
+ "grad_norm": 1.0859375,
1087
+ "learning_rate": 0.0001938169793717286,
1088
+ "loss": 4.9598,
1089
+ "step": 152
1090
+ },
1091
+ {
1092
+ "epoch": 0.48056537102473496,
1093
+ "grad_norm": 1.15625,
1094
+ "learning_rate": 0.0001937305126811437,
1095
+ "loss": 5.1067,
1096
+ "step": 153
1097
+ },
1098
+ {
1099
+ "epoch": 0.48370632116215156,
1100
+ "grad_norm": 0.7890625,
1101
+ "learning_rate": 0.0001936434651434876,
1102
+ "loss": 5.1599,
1103
+ "step": 154
1104
+ },
1105
+ {
1106
+ "epoch": 0.4868472712995681,
1107
+ "grad_norm": 1.109375,
1108
+ "learning_rate": 0.00019355583729819317,
1109
+ "loss": 4.9971,
1110
+ "step": 155
1111
+ },
1112
+ {
1113
+ "epoch": 0.48998822143698467,
1114
+ "grad_norm": 1.25,
1115
+ "learning_rate": 0.0001934676296882892,
1116
+ "loss": 5.0528,
1117
+ "step": 156
1118
+ },
1119
+ {
1120
+ "epoch": 0.4931291715744013,
1121
+ "grad_norm": 1.0390625,
1122
+ "learning_rate": 0.00019337884286039746,
1123
+ "loss": 5.2021,
1124
+ "step": 157
1125
+ },
1126
+ {
1127
+ "epoch": 0.49627012171181784,
1128
+ "grad_norm": 1.015625,
1129
+ "learning_rate": 0.00019328947736472904,
1130
+ "loss": 4.7814,
1131
+ "step": 158
1132
+ },
1133
+ {
1134
+ "epoch": 0.4994110718492344,
1135
+ "grad_norm": 1.0,
1136
+ "learning_rate": 0.00019319953375508106,
1137
+ "loss": 5.0906,
1138
+ "step": 159
1139
+ },
1140
+ {
1141
+ "epoch": 0.5025520219866509,
1142
+ "grad_norm": 0.91015625,
1143
+ "learning_rate": 0.00019310901258883317,
1144
+ "loss": 5.0323,
1145
+ "step": 160
1146
+ },
1147
+ {
1148
+ "epoch": 0.5025520219866509,
1149
+ "eval_loss": 5.075822353363037,
1150
+ "eval_runtime": 66.934,
1151
+ "eval_samples_per_second": 38.859,
1152
+ "eval_steps_per_second": 38.859,
1153
+ "step": 160
1154
+ },
1155
+ {
1156
+ "epoch": 0.5056929721240675,
1157
+ "grad_norm": 0.921875,
1158
+ "learning_rate": 0.00019301791442694413,
1159
+ "loss": 5.1209,
1160
+ "step": 161
1161
+ },
1162
+ {
1163
+ "epoch": 0.508833922261484,
1164
+ "grad_norm": 2.765625,
1165
+ "learning_rate": 0.00019292623983394838,
1166
+ "loss": 5.0187,
1167
+ "step": 162
1168
+ },
1169
+ {
1170
+ "epoch": 0.5119748723989007,
1171
+ "grad_norm": 1.234375,
1172
+ "learning_rate": 0.0001928339893779525,
1173
+ "loss": 4.9584,
1174
+ "step": 163
1175
+ },
1176
+ {
1177
+ "epoch": 0.5151158225363173,
1178
+ "grad_norm": 1.28125,
1179
+ "learning_rate": 0.00019274116363063163,
1180
+ "loss": 4.9459,
1181
+ "step": 164
1182
+ },
1183
+ {
1184
+ "epoch": 0.5182567726737338,
1185
+ "grad_norm": 0.859375,
1186
+ "learning_rate": 0.00019264776316722603,
1187
+ "loss": 4.7699,
1188
+ "step": 165
1189
+ },
1190
+ {
1191
+ "epoch": 0.5213977228111504,
1192
+ "grad_norm": 1.0625,
1193
+ "learning_rate": 0.00019255378856653746,
1194
+ "loss": 5.0324,
1195
+ "step": 166
1196
+ },
1197
+ {
1198
+ "epoch": 0.5245386729485669,
1199
+ "grad_norm": 1.15625,
1200
+ "learning_rate": 0.00019245924041092562,
1201
+ "loss": 5.2702,
1202
+ "step": 167
1203
+ },
1204
+ {
1205
+ "epoch": 0.5276796230859835,
1206
+ "grad_norm": 1.0703125,
1207
+ "learning_rate": 0.00019236411928630446,
1208
+ "loss": 5.0989,
1209
+ "step": 168
1210
+ },
1211
+ {
1212
+ "epoch": 0.5308205732234,
1213
+ "grad_norm": 0.93359375,
1214
+ "learning_rate": 0.00019226842578213874,
1215
+ "loss": 4.7667,
1216
+ "step": 169
1217
+ },
1218
+ {
1219
+ "epoch": 0.5339615233608166,
1220
+ "grad_norm": 0.99609375,
1221
+ "learning_rate": 0.00019217216049144007,
1222
+ "loss": 4.8303,
1223
+ "step": 170
1224
+ },
1225
+ {
1226
+ "epoch": 0.5371024734982333,
1227
+ "grad_norm": 0.8984375,
1228
+ "learning_rate": 0.00019207532401076358,
1229
+ "loss": 5.0607,
1230
+ "step": 171
1231
+ },
1232
+ {
1233
+ "epoch": 0.5402434236356498,
1234
+ "grad_norm": 1.0390625,
1235
+ "learning_rate": 0.00019197791694020396,
1236
+ "loss": 4.96,
1237
+ "step": 172
1238
+ },
1239
+ {
1240
+ "epoch": 0.5433843737730664,
1241
+ "grad_norm": 0.91796875,
1242
+ "learning_rate": 0.00019187993988339192,
1243
+ "loss": 5.0107,
1244
+ "step": 173
1245
+ },
1246
+ {
1247
+ "epoch": 0.5465253239104829,
1248
+ "grad_norm": 1.2578125,
1249
+ "learning_rate": 0.0001917813934474903,
1250
+ "loss": 5.1961,
1251
+ "step": 174
1252
+ },
1253
+ {
1254
+ "epoch": 0.5496662740478995,
1255
+ "grad_norm": 1.0546875,
1256
+ "learning_rate": 0.0001916822782431904,
1257
+ "loss": 5.0727,
1258
+ "step": 175
1259
+ },
1260
+ {
1261
+ "epoch": 0.552807224185316,
1262
+ "grad_norm": 1.203125,
1263
+ "learning_rate": 0.00019158259488470815,
1264
+ "loss": 4.8185,
1265
+ "step": 176
1266
+ },
1267
+ {
1268
+ "epoch": 0.5559481743227326,
1269
+ "grad_norm": 1.59375,
1270
+ "learning_rate": 0.00019148234398978038,
1271
+ "loss": 5.2447,
1272
+ "step": 177
1273
+ },
1274
+ {
1275
+ "epoch": 0.5590891244601492,
1276
+ "grad_norm": 1.25,
1277
+ "learning_rate": 0.0001913815261796609,
1278
+ "loss": 5.0844,
1279
+ "step": 178
1280
+ },
1281
+ {
1282
+ "epoch": 0.5622300745975658,
1283
+ "grad_norm": 1.0390625,
1284
+ "learning_rate": 0.0001912801420791167,
1285
+ "loss": 5.0112,
1286
+ "step": 179
1287
+ },
1288
+ {
1289
+ "epoch": 0.5653710247349824,
1290
+ "grad_norm": 1.3671875,
1291
+ "learning_rate": 0.000191178192316424,
1292
+ "loss": 5.1335,
1293
+ "step": 180
1294
+ },
1295
+ {
1296
+ "epoch": 0.5685119748723989,
1297
+ "grad_norm": 1.2734375,
1298
+ "learning_rate": 0.00019107567752336458,
1299
+ "loss": 5.1664,
1300
+ "step": 181
1301
+ },
1302
+ {
1303
+ "epoch": 0.5716529250098155,
1304
+ "grad_norm": 0.90625,
1305
+ "learning_rate": 0.0001909725983352215,
1306
+ "loss": 4.9254,
1307
+ "step": 182
1308
+ },
1309
+ {
1310
+ "epoch": 0.574793875147232,
1311
+ "grad_norm": 0.8515625,
1312
+ "learning_rate": 0.00019086895539077562,
1313
+ "loss": 4.8303,
1314
+ "step": 183
1315
+ },
1316
+ {
1317
+ "epoch": 0.5779348252846486,
1318
+ "grad_norm": 1.2734375,
1319
+ "learning_rate": 0.00019076474933230116,
1320
+ "loss": 4.9595,
1321
+ "step": 184
1322
+ },
1323
+ {
1324
+ "epoch": 0.5810757754220651,
1325
+ "grad_norm": 1.3046875,
1326
+ "learning_rate": 0.00019065998080556204,
1327
+ "loss": 5.0253,
1328
+ "step": 185
1329
+ },
1330
+ {
1331
+ "epoch": 0.5842167255594818,
1332
+ "grad_norm": 1.078125,
1333
+ "learning_rate": 0.00019055465045980782,
1334
+ "loss": 5.1003,
1335
+ "step": 186
1336
+ },
1337
+ {
1338
+ "epoch": 0.5873576756968983,
1339
+ "grad_norm": 1.0703125,
1340
+ "learning_rate": 0.00019044875894776966,
1341
+ "loss": 4.9631,
1342
+ "step": 187
1343
+ },
1344
+ {
1345
+ "epoch": 0.5904986258343149,
1346
+ "grad_norm": 1.1171875,
1347
+ "learning_rate": 0.00019034230692565614,
1348
+ "loss": 4.9462,
1349
+ "step": 188
1350
+ },
1351
+ {
1352
+ "epoch": 0.5936395759717314,
1353
+ "grad_norm": 1.4453125,
1354
+ "learning_rate": 0.0001902352950531495,
1355
+ "loss": 4.8688,
1356
+ "step": 189
1357
+ },
1358
+ {
1359
+ "epoch": 0.596780526109148,
1360
+ "grad_norm": 1.3359375,
1361
+ "learning_rate": 0.0001901277239934012,
1362
+ "loss": 5.1219,
1363
+ "step": 190
1364
+ },
1365
+ {
1366
+ "epoch": 0.5999214762465646,
1367
+ "grad_norm": 1.2109375,
1368
+ "learning_rate": 0.00019001959441302806,
1369
+ "loss": 5.0382,
1370
+ "step": 191
1371
+ },
1372
+ {
1373
+ "epoch": 0.6030624263839811,
1374
+ "grad_norm": 1.2109375,
1375
+ "learning_rate": 0.00018991090698210802,
1376
+ "loss": 4.9474,
1377
+ "step": 192
1378
+ },
1379
+ {
1380
+ "epoch": 0.6062033765213978,
1381
+ "grad_norm": 1.2734375,
1382
+ "learning_rate": 0.00018980166237417606,
1383
+ "loss": 5.034,
1384
+ "step": 193
1385
+ },
1386
+ {
1387
+ "epoch": 0.6093443266588143,
1388
+ "grad_norm": 1.1875,
1389
+ "learning_rate": 0.00018969186126621996,
1390
+ "loss": 5.0142,
1391
+ "step": 194
1392
+ },
1393
+ {
1394
+ "epoch": 0.6124852767962309,
1395
+ "grad_norm": 1.203125,
1396
+ "learning_rate": 0.00018958150433867605,
1397
+ "loss": 4.7944,
1398
+ "step": 195
1399
+ },
1400
+ {
1401
+ "epoch": 0.6156262269336474,
1402
+ "grad_norm": 1.0078125,
1403
+ "learning_rate": 0.0001894705922754252,
1404
+ "loss": 4.7905,
1405
+ "step": 196
1406
+ },
1407
+ {
1408
+ "epoch": 0.618767177071064,
1409
+ "grad_norm": 0.92578125,
1410
+ "learning_rate": 0.0001893591257637883,
1411
+ "loss": 4.8537,
1412
+ "step": 197
1413
+ },
1414
+ {
1415
+ "epoch": 0.6219081272084805,
1416
+ "grad_norm": 1.15625,
1417
+ "learning_rate": 0.00018924710549452232,
1418
+ "loss": 4.8625,
1419
+ "step": 198
1420
+ },
1421
+ {
1422
+ "epoch": 0.6250490773458971,
1423
+ "grad_norm": 1.2421875,
1424
+ "learning_rate": 0.0001891345321618157,
1425
+ "loss": 5.1188,
1426
+ "step": 199
1427
+ },
1428
+ {
1429
+ "epoch": 0.6281900274833137,
1430
+ "grad_norm": 0.9921875,
1431
+ "learning_rate": 0.00018902140646328435,
1432
+ "loss": 4.7798,
1433
+ "step": 200
1434
+ },
1435
+ {
1436
+ "epoch": 0.6313309776207303,
1437
+ "grad_norm": 1.234375,
1438
+ "learning_rate": 0.0001889077290999671,
1439
+ "loss": 4.9184,
1440
+ "step": 201
1441
+ },
1442
+ {
1443
+ "epoch": 0.6344719277581469,
1444
+ "grad_norm": 1.375,
1445
+ "learning_rate": 0.00018879350077632143,
1446
+ "loss": 5.0932,
1447
+ "step": 202
1448
+ },
1449
+ {
1450
+ "epoch": 0.6376128778955634,
1451
+ "grad_norm": 1.0234375,
1452
+ "learning_rate": 0.00018867872220021913,
1453
+ "loss": 4.9846,
1454
+ "step": 203
1455
+ },
1456
+ {
1457
+ "epoch": 0.64075382803298,
1458
+ "grad_norm": 1.3203125,
1459
+ "learning_rate": 0.00018856339408294202,
1460
+ "loss": 4.8107,
1461
+ "step": 204
1462
+ },
1463
+ {
1464
+ "epoch": 0.6438947781703965,
1465
+ "grad_norm": 1.0625,
1466
+ "learning_rate": 0.0001884475171391772,
1467
+ "loss": 4.9413,
1468
+ "step": 205
1469
+ },
1470
+ {
1471
+ "epoch": 0.6470357283078131,
1472
+ "grad_norm": 1.0078125,
1473
+ "learning_rate": 0.00018833109208701298,
1474
+ "loss": 4.9209,
1475
+ "step": 206
1476
+ },
1477
+ {
1478
+ "epoch": 0.6501766784452296,
1479
+ "grad_norm": 1.1171875,
1480
+ "learning_rate": 0.00018821411964793433,
1481
+ "loss": 4.8073,
1482
+ "step": 207
1483
+ },
1484
+ {
1485
+ "epoch": 0.6533176285826463,
1486
+ "grad_norm": 1.1953125,
1487
+ "learning_rate": 0.00018809660054681823,
1488
+ "loss": 4.7729,
1489
+ "step": 208
1490
+ },
1491
+ {
1492
+ "epoch": 0.6564585787200629,
1493
+ "grad_norm": 1.046875,
1494
+ "learning_rate": 0.0001879785355119295,
1495
+ "loss": 5.0412,
1496
+ "step": 209
1497
+ },
1498
+ {
1499
+ "epoch": 0.6595995288574794,
1500
+ "grad_norm": 2.515625,
1501
+ "learning_rate": 0.0001878599252749159,
1502
+ "loss": 4.8707,
1503
+ "step": 210
1504
+ },
1505
+ {
1506
+ "epoch": 0.662740478994896,
1507
+ "grad_norm": 1.6015625,
1508
+ "learning_rate": 0.00018774077057080398,
1509
+ "loss": 4.6271,
1510
+ "step": 211
1511
+ },
1512
+ {
1513
+ "epoch": 0.6658814291323125,
1514
+ "grad_norm": 1.359375,
1515
+ "learning_rate": 0.00018762107213799427,
1516
+ "loss": 4.8702,
1517
+ "step": 212
1518
+ },
1519
+ {
1520
+ "epoch": 0.6690223792697291,
1521
+ "grad_norm": 1.2578125,
1522
+ "learning_rate": 0.00018750083071825677,
1523
+ "loss": 4.8727,
1524
+ "step": 213
1525
+ },
1526
+ {
1527
+ "epoch": 0.6721633294071456,
1528
+ "grad_norm": 1.71875,
1529
+ "learning_rate": 0.0001873800470567264,
1530
+ "loss": 4.8376,
1531
+ "step": 214
1532
+ },
1533
+ {
1534
+ "epoch": 0.6753042795445622,
1535
+ "grad_norm": 1.7421875,
1536
+ "learning_rate": 0.00018725872190189827,
1537
+ "loss": 4.8666,
1538
+ "step": 215
1539
+ },
1540
+ {
1541
+ "epoch": 0.6784452296819788,
1542
+ "grad_norm": 1.1875,
1543
+ "learning_rate": 0.00018713685600562328,
1544
+ "loss": 5.038,
1545
+ "step": 216
1546
+ },
1547
+ {
1548
+ "epoch": 0.6815861798193954,
1549
+ "grad_norm": 1.0546875,
1550
+ "learning_rate": 0.00018701445012310315,
1551
+ "loss": 4.9007,
1552
+ "step": 217
1553
+ },
1554
+ {
1555
+ "epoch": 0.684727129956812,
1556
+ "grad_norm": 1.1875,
1557
+ "learning_rate": 0.00018689150501288593,
1558
+ "loss": 4.8299,
1559
+ "step": 218
1560
+ },
1561
+ {
1562
+ "epoch": 0.6878680800942285,
1563
+ "grad_norm": 1.3125,
1564
+ "learning_rate": 0.00018676802143686126,
1565
+ "loss": 4.801,
1566
+ "step": 219
1567
+ },
1568
+ {
1569
+ "epoch": 0.6910090302316451,
1570
+ "grad_norm": 1.2109375,
1571
+ "learning_rate": 0.00018664400016025568,
1572
+ "loss": 4.7097,
1573
+ "step": 220
1574
+ },
1575
+ {
1576
+ "epoch": 0.6941499803690616,
1577
+ "grad_norm": 1.6796875,
1578
+ "learning_rate": 0.00018651944195162778,
1579
+ "loss": 4.8088,
1580
+ "step": 221
1581
+ },
1582
+ {
1583
+ "epoch": 0.6972909305064782,
1584
+ "grad_norm": 1.25,
1585
+ "learning_rate": 0.0001863943475828636,
1586
+ "loss": 4.9253,
1587
+ "step": 222
1588
+ },
1589
+ {
1590
+ "epoch": 0.7004318806438948,
1591
+ "grad_norm": 1.40625,
1592
+ "learning_rate": 0.00018626871782917174,
1593
+ "loss": 4.8615,
1594
+ "step": 223
1595
+ },
1596
+ {
1597
+ "epoch": 0.7035728307813114,
1598
+ "grad_norm": 1.1328125,
1599
+ "learning_rate": 0.00018614255346907855,
1600
+ "loss": 4.7592,
1601
+ "step": 224
1602
+ },
1603
+ {
1604
+ "epoch": 0.7067137809187279,
1605
+ "grad_norm": 1.5,
1606
+ "learning_rate": 0.0001860158552844233,
1607
+ "loss": 4.6569,
1608
+ "step": 225
1609
+ },
1610
+ {
1611
+ "epoch": 0.7098547310561445,
1612
+ "grad_norm": 1.59375,
1613
+ "learning_rate": 0.0001858886240603534,
1614
+ "loss": 4.8259,
1615
+ "step": 226
1616
+ },
1617
+ {
1618
+ "epoch": 0.712995681193561,
1619
+ "grad_norm": 1.53125,
1620
+ "learning_rate": 0.00018576086058531957,
1621
+ "loss": 4.8066,
1622
+ "step": 227
1623
+ },
1624
+ {
1625
+ "epoch": 0.7161366313309776,
1626
+ "grad_norm": 1.3828125,
1627
+ "learning_rate": 0.00018563256565107072,
1628
+ "loss": 4.8039,
1629
+ "step": 228
1630
+ },
1631
+ {
1632
+ "epoch": 0.7192775814683942,
1633
+ "grad_norm": 1.390625,
1634
+ "learning_rate": 0.00018550374005264937,
1635
+ "loss": 4.8336,
1636
+ "step": 229
1637
+ },
1638
+ {
1639
+ "epoch": 0.7224185316058107,
1640
+ "grad_norm": 1.4765625,
1641
+ "learning_rate": 0.0001853743845883865,
1642
+ "loss": 4.7032,
1643
+ "step": 230
1644
+ },
1645
+ {
1646
+ "epoch": 0.7255594817432274,
1647
+ "grad_norm": 1.5078125,
1648
+ "learning_rate": 0.0001852445000598966,
1649
+ "loss": 4.827,
1650
+ "step": 231
1651
+ },
1652
+ {
1653
+ "epoch": 0.7287004318806439,
1654
+ "grad_norm": 1.2578125,
1655
+ "learning_rate": 0.0001851140872720729,
1656
+ "loss": 4.996,
1657
+ "step": 232
1658
+ },
1659
+ {
1660
+ "epoch": 0.7318413820180605,
1661
+ "grad_norm": 1.7109375,
1662
+ "learning_rate": 0.0001849831470330821,
1663
+ "loss": 4.7288,
1664
+ "step": 233
1665
+ },
1666
+ {
1667
+ "epoch": 0.734982332155477,
1668
+ "grad_norm": 1.6796875,
1669
+ "learning_rate": 0.00018485168015435966,
1670
+ "loss": 4.8204,
1671
+ "step": 234
1672
+ },
1673
+ {
1674
+ "epoch": 0.7381232822928936,
1675
+ "grad_norm": 1.5546875,
1676
+ "learning_rate": 0.00018471968745060444,
1677
+ "loss": 4.8829,
1678
+ "step": 235
1679
+ },
1680
+ {
1681
+ "epoch": 0.7412642324303101,
1682
+ "grad_norm": 1.5234375,
1683
+ "learning_rate": 0.00018458716973977405,
1684
+ "loss": 4.7297,
1685
+ "step": 236
1686
+ },
1687
+ {
1688
+ "epoch": 0.7444051825677267,
1689
+ "grad_norm": 1.6640625,
1690
+ "learning_rate": 0.00018445412784307932,
1691
+ "loss": 4.7916,
1692
+ "step": 237
1693
+ },
1694
+ {
1695
+ "epoch": 0.7475461327051433,
1696
+ "grad_norm": 1.265625,
1697
+ "learning_rate": 0.0001843205625849797,
1698
+ "loss": 4.5585,
1699
+ "step": 238
1700
+ },
1701
+ {
1702
+ "epoch": 0.7506870828425599,
1703
+ "grad_norm": 1.5234375,
1704
+ "learning_rate": 0.00018418647479317776,
1705
+ "loss": 4.9319,
1706
+ "step": 239
1707
+ },
1708
+ {
1709
+ "epoch": 0.7538280329799765,
1710
+ "grad_norm": 1.6796875,
1711
+ "learning_rate": 0.00018405186529861416,
1712
+ "loss": 4.9877,
1713
+ "step": 240
1714
+ },
1715
+ {
1716
+ "epoch": 0.7538280329799765,
1717
+ "eval_loss": 4.841662406921387,
1718
+ "eval_runtime": 66.8839,
1719
+ "eval_samples_per_second": 38.888,
1720
+ "eval_steps_per_second": 38.888,
1721
+ "step": 240
1722
+ },
1723
+ {
1724
+ "epoch": 0.756968983117393,
1725
+ "grad_norm": 1.375,
1726
+ "learning_rate": 0.00018391673493546273,
1727
+ "loss": 4.7421,
1728
+ "step": 241
1729
+ },
1730
+ {
1731
+ "epoch": 0.7601099332548096,
1732
+ "grad_norm": 1.265625,
1733
+ "learning_rate": 0.00018378108454112494,
1734
+ "loss": 4.6469,
1735
+ "step": 242
1736
+ },
1737
+ {
1738
+ "epoch": 0.7632508833922261,
1739
+ "grad_norm": 2.109375,
1740
+ "learning_rate": 0.00018364491495622497,
1741
+ "loss": 4.7609,
1742
+ "step": 243
1743
+ },
1744
+ {
1745
+ "epoch": 0.7663918335296427,
1746
+ "grad_norm": 1.3203125,
1747
+ "learning_rate": 0.00018350822702460444,
1748
+ "loss": 4.737,
1749
+ "step": 244
1750
+ },
1751
+ {
1752
+ "epoch": 0.7695327836670592,
1753
+ "grad_norm": 1.7734375,
1754
+ "learning_rate": 0.0001833710215933171,
1755
+ "loss": 4.7964,
1756
+ "step": 245
1757
+ },
1758
+ {
1759
+ "epoch": 0.7726737338044759,
1760
+ "grad_norm": 1.6640625,
1761
+ "learning_rate": 0.00018323329951262367,
1762
+ "loss": 4.8785,
1763
+ "step": 246
1764
+ },
1765
+ {
1766
+ "epoch": 0.7758146839418925,
1767
+ "grad_norm": 1.7421875,
1768
+ "learning_rate": 0.0001830950616359865,
1769
+ "loss": 4.83,
1770
+ "step": 247
1771
+ },
1772
+ {
1773
+ "epoch": 0.778955634079309,
1774
+ "grad_norm": 1.53125,
1775
+ "learning_rate": 0.00018295630882006445,
1776
+ "loss": 4.9096,
1777
+ "step": 248
1778
+ },
1779
+ {
1780
+ "epoch": 0.7820965842167256,
1781
+ "grad_norm": 1.6484375,
1782
+ "learning_rate": 0.00018281704192470727,
1783
+ "loss": 4.7864,
1784
+ "step": 249
1785
+ },
1786
+ {
1787
+ "epoch": 0.7852375343541421,
1788
+ "grad_norm": 1.5078125,
1789
+ "learning_rate": 0.00018267726181295065,
1790
+ "loss": 4.8557,
1791
+ "step": 250
1792
+ },
1793
+ {
1794
+ "epoch": 0.7883784844915587,
1795
+ "grad_norm": 2.578125,
1796
+ "learning_rate": 0.00018253696935101047,
1797
+ "loss": 4.8157,
1798
+ "step": 251
1799
+ },
1800
+ {
1801
+ "epoch": 0.7915194346289752,
1802
+ "grad_norm": 2.21875,
1803
+ "learning_rate": 0.00018239616540827782,
1804
+ "loss": 4.8016,
1805
+ "step": 252
1806
+ },
1807
+ {
1808
+ "epoch": 0.7946603847663918,
1809
+ "grad_norm": 1.390625,
1810
+ "learning_rate": 0.0001822548508573133,
1811
+ "loss": 4.657,
1812
+ "step": 253
1813
+ },
1814
+ {
1815
+ "epoch": 0.7978013349038084,
1816
+ "grad_norm": 2.21875,
1817
+ "learning_rate": 0.00018211302657384186,
1818
+ "loss": 4.7423,
1819
+ "step": 254
1820
+ },
1821
+ {
1822
+ "epoch": 0.800942285041225,
1823
+ "grad_norm": 2.328125,
1824
+ "learning_rate": 0.00018197069343674715,
1825
+ "loss": 4.8695,
1826
+ "step": 255
1827
+ },
1828
+ {
1829
+ "epoch": 0.8040832351786416,
1830
+ "grad_norm": 1.7421875,
1831
+ "learning_rate": 0.00018182785232806627,
1832
+ "loss": 4.9817,
1833
+ "step": 256
1834
+ },
1835
+ {
1836
+ "epoch": 0.8072241853160581,
1837
+ "grad_norm": 2.125,
1838
+ "learning_rate": 0.00018168450413298416,
1839
+ "loss": 4.794,
1840
+ "step": 257
1841
+ },
1842
+ {
1843
+ "epoch": 0.8103651354534747,
1844
+ "grad_norm": 1.9921875,
1845
+ "learning_rate": 0.00018154064973982816,
1846
+ "loss": 4.9111,
1847
+ "step": 258
1848
+ },
1849
+ {
1850
+ "epoch": 0.8135060855908912,
1851
+ "grad_norm": 2.0625,
1852
+ "learning_rate": 0.0001813962900400626,
1853
+ "loss": 4.9169,
1854
+ "step": 259
1855
+ },
1856
+ {
1857
+ "epoch": 0.8166470357283078,
1858
+ "grad_norm": 1.765625,
1859
+ "learning_rate": 0.00018125142592828307,
1860
+ "loss": 4.7243,
1861
+ "step": 260
1862
+ },
1863
+ {
1864
+ "epoch": 0.8197879858657244,
1865
+ "grad_norm": 2.234375,
1866
+ "learning_rate": 0.00018110605830221104,
1867
+ "loss": 4.8339,
1868
+ "step": 261
1869
+ },
1870
+ {
1871
+ "epoch": 0.822928936003141,
1872
+ "grad_norm": 1.9609375,
1873
+ "learning_rate": 0.00018096018806268834,
1874
+ "loss": 4.6423,
1875
+ "step": 262
1876
+ },
1877
+ {
1878
+ "epoch": 0.8260698861405575,
1879
+ "grad_norm": 1.9453125,
1880
+ "learning_rate": 0.00018081381611367134,
1881
+ "loss": 4.6603,
1882
+ "step": 263
1883
+ },
1884
+ {
1885
+ "epoch": 0.8292108362779741,
1886
+ "grad_norm": 2.359375,
1887
+ "learning_rate": 0.00018066694336222564,
1888
+ "loss": 4.8327,
1889
+ "step": 264
1890
+ },
1891
+ {
1892
+ "epoch": 0.8323517864153906,
1893
+ "grad_norm": 2.765625,
1894
+ "learning_rate": 0.0001805195707185202,
1895
+ "loss": 4.7741,
1896
+ "step": 265
1897
+ },
1898
+ {
1899
+ "epoch": 0.8354927365528072,
1900
+ "grad_norm": 2.453125,
1901
+ "learning_rate": 0.00018037169909582192,
1902
+ "loss": 4.8735,
1903
+ "step": 266
1904
+ },
1905
+ {
1906
+ "epoch": 0.8386336866902238,
1907
+ "grad_norm": 1.9375,
1908
+ "learning_rate": 0.00018022332941048972,
1909
+ "loss": 4.5862,
1910
+ "step": 267
1911
+ },
1912
+ {
1913
+ "epoch": 0.8417746368276403,
1914
+ "grad_norm": 2.453125,
1915
+ "learning_rate": 0.00018007446258196916,
1916
+ "loss": 4.6305,
1917
+ "step": 268
1918
+ },
1919
+ {
1920
+ "epoch": 0.844915586965057,
1921
+ "grad_norm": 1.8046875,
1922
+ "learning_rate": 0.00017992509953278644,
1923
+ "loss": 4.7259,
1924
+ "step": 269
1925
+ },
1926
+ {
1927
+ "epoch": 0.8480565371024735,
1928
+ "grad_norm": 1.9765625,
1929
+ "learning_rate": 0.000179775241188543,
1930
+ "loss": 4.7171,
1931
+ "step": 270
1932
+ },
1933
+ {
1934
+ "epoch": 0.8511974872398901,
1935
+ "grad_norm": 1.8984375,
1936
+ "learning_rate": 0.0001796248884779095,
1937
+ "loss": 4.5035,
1938
+ "step": 271
1939
+ },
1940
+ {
1941
+ "epoch": 0.8543384373773066,
1942
+ "grad_norm": 1.7265625,
1943
+ "learning_rate": 0.0001794740423326202,
1944
+ "loss": 4.5654,
1945
+ "step": 272
1946
+ },
1947
+ {
1948
+ "epoch": 0.8574793875147232,
1949
+ "grad_norm": 2.234375,
1950
+ "learning_rate": 0.00017932270368746723,
1951
+ "loss": 4.7109,
1952
+ "step": 273
1953
+ },
1954
+ {
1955
+ "epoch": 0.8606203376521397,
1956
+ "grad_norm": 2.09375,
1957
+ "learning_rate": 0.00017917087348029464,
1958
+ "loss": 4.6446,
1959
+ "step": 274
1960
+ },
1961
+ {
1962
+ "epoch": 0.8637612877895563,
1963
+ "grad_norm": 2.171875,
1964
+ "learning_rate": 0.0001790185526519928,
1965
+ "loss": 4.6444,
1966
+ "step": 275
1967
+ },
1968
+ {
1969
+ "epoch": 0.866902237926973,
1970
+ "grad_norm": 1.8984375,
1971
+ "learning_rate": 0.00017886574214649235,
1972
+ "loss": 4.6852,
1973
+ "step": 276
1974
+ },
1975
+ {
1976
+ "epoch": 0.8700431880643895,
1977
+ "grad_norm": 2.09375,
1978
+ "learning_rate": 0.0001787124429107585,
1979
+ "loss": 4.6116,
1980
+ "step": 277
1981
+ },
1982
+ {
1983
+ "epoch": 0.8731841382018061,
1984
+ "grad_norm": 1.875,
1985
+ "learning_rate": 0.00017855865589478515,
1986
+ "loss": 4.7119,
1987
+ "step": 278
1988
+ },
1989
+ {
1990
+ "epoch": 0.8763250883392226,
1991
+ "grad_norm": 2.0625,
1992
+ "learning_rate": 0.00017840438205158891,
1993
+ "loss": 4.7154,
1994
+ "step": 279
1995
+ },
1996
+ {
1997
+ "epoch": 0.8794660384766392,
1998
+ "grad_norm": 2.171875,
1999
+ "learning_rate": 0.00017824962233720332,
2000
+ "loss": 4.7945,
2001
+ "step": 280
2002
+ },
2003
+ {
2004
+ "epoch": 0.8826069886140557,
2005
+ "grad_norm": 2.828125,
2006
+ "learning_rate": 0.00017809437771067272,
2007
+ "loss": 4.7312,
2008
+ "step": 281
2009
+ },
2010
+ {
2011
+ "epoch": 0.8857479387514723,
2012
+ "grad_norm": 2.109375,
2013
+ "learning_rate": 0.00017793864913404663,
2014
+ "loss": 4.5674,
2015
+ "step": 282
2016
+ },
2017
+ {
2018
+ "epoch": 0.8888888888888888,
2019
+ "grad_norm": 2.203125,
2020
+ "learning_rate": 0.00017778243757237352,
2021
+ "loss": 4.6855,
2022
+ "step": 283
2023
+ },
2024
+ {
2025
+ "epoch": 0.8920298390263055,
2026
+ "grad_norm": 2.40625,
2027
+ "learning_rate": 0.00017762574399369485,
2028
+ "loss": 4.7105,
2029
+ "step": 284
2030
+ },
2031
+ {
2032
+ "epoch": 0.8951707891637221,
2033
+ "grad_norm": 2.171875,
2034
+ "learning_rate": 0.00017746856936903926,
2035
+ "loss": 4.7111,
2036
+ "step": 285
2037
+ },
2038
+ {
2039
+ "epoch": 0.8983117393011386,
2040
+ "grad_norm": 1.984375,
2041
+ "learning_rate": 0.0001773109146724163,
2042
+ "loss": 4.7511,
2043
+ "step": 286
2044
+ },
2045
+ {
2046
+ "epoch": 0.9014526894385552,
2047
+ "grad_norm": 2.34375,
2048
+ "learning_rate": 0.00017715278088081062,
2049
+ "loss": 4.7156,
2050
+ "step": 287
2051
+ },
2052
+ {
2053
+ "epoch": 0.9045936395759717,
2054
+ "grad_norm": 2.796875,
2055
+ "learning_rate": 0.0001769941689741758,
2056
+ "loss": 4.7225,
2057
+ "step": 288
2058
+ },
2059
+ {
2060
+ "epoch": 0.9077345897133883,
2061
+ "grad_norm": 2.703125,
2062
+ "learning_rate": 0.00017683507993542825,
2063
+ "loss": 4.7426,
2064
+ "step": 289
2065
+ },
2066
+ {
2067
+ "epoch": 0.9108755398508048,
2068
+ "grad_norm": 2.4375,
2069
+ "learning_rate": 0.0001766755147504412,
2070
+ "loss": 4.8524,
2071
+ "step": 290
2072
+ },
2073
+ {
2074
+ "epoch": 0.9140164899882215,
2075
+ "grad_norm": 2.65625,
2076
+ "learning_rate": 0.00017651547440803851,
2077
+ "loss": 4.6249,
2078
+ "step": 291
2079
+ },
2080
+ {
2081
+ "epoch": 0.917157440125638,
2082
+ "grad_norm": 3.125,
2083
+ "learning_rate": 0.00017635495989998864,
2084
+ "loss": 4.8815,
2085
+ "step": 292
2086
+ },
2087
+ {
2088
+ "epoch": 0.9202983902630546,
2089
+ "grad_norm": 2.71875,
2090
+ "learning_rate": 0.00017619397222099848,
2091
+ "loss": 4.7107,
2092
+ "step": 293
2093
+ },
2094
+ {
2095
+ "epoch": 0.9234393404004712,
2096
+ "grad_norm": 2.53125,
2097
+ "learning_rate": 0.00017603251236870702,
2098
+ "loss": 4.5988,
2099
+ "step": 294
2100
+ },
2101
+ {
2102
+ "epoch": 0.9265802905378877,
2103
+ "grad_norm": 2.703125,
2104
+ "learning_rate": 0.0001758705813436794,
2105
+ "loss": 4.43,
2106
+ "step": 295
2107
+ },
2108
+ {
2109
+ "epoch": 0.9297212406753043,
2110
+ "grad_norm": 2.84375,
2111
+ "learning_rate": 0.00017570818014940064,
2112
+ "loss": 4.8238,
2113
+ "step": 296
2114
+ },
2115
+ {
2116
+ "epoch": 0.9328621908127208,
2117
+ "grad_norm": 2.578125,
2118
+ "learning_rate": 0.00017554530979226933,
2119
+ "loss": 4.7022,
2120
+ "step": 297
2121
+ },
2122
+ {
2123
+ "epoch": 0.9360031409501374,
2124
+ "grad_norm": 2.96875,
2125
+ "learning_rate": 0.00017538197128159148,
2126
+ "loss": 4.8184,
2127
+ "step": 298
2128
+ },
2129
+ {
2130
+ "epoch": 0.939144091087554,
2131
+ "grad_norm": 2.609375,
2132
+ "learning_rate": 0.00017521816562957428,
2133
+ "loss": 4.4714,
2134
+ "step": 299
2135
+ },
2136
+ {
2137
+ "epoch": 0.9422850412249706,
2138
+ "grad_norm": 2.40625,
2139
+ "learning_rate": 0.00017505389385131972,
2140
+ "loss": 4.4407,
2141
+ "step": 300
2142
+ },
2143
+ {
2144
+ "epoch": 0.9454259913623871,
2145
+ "grad_norm": 3.25,
2146
+ "learning_rate": 0.00017488915696481838,
2147
+ "loss": 4.6623,
2148
+ "step": 301
2149
+ },
2150
+ {
2151
+ "epoch": 0.9485669414998037,
2152
+ "grad_norm": 2.109375,
2153
+ "learning_rate": 0.00017472395599094317,
2154
+ "loss": 4.6181,
2155
+ "step": 302
2156
+ },
2157
+ {
2158
+ "epoch": 0.9517078916372202,
2159
+ "grad_norm": 2.890625,
2160
+ "learning_rate": 0.00017455829195344293,
2161
+ "loss": 4.6449,
2162
+ "step": 303
2163
+ },
2164
+ {
2165
+ "epoch": 0.9548488417746368,
2166
+ "grad_norm": 6.84375,
2167
+ "learning_rate": 0.00017439216587893604,
2168
+ "loss": 4.538,
2169
+ "step": 304
2170
+ },
2171
+ {
2172
+ "epoch": 0.9579897919120534,
2173
+ "grad_norm": 3.5625,
2174
+ "learning_rate": 0.0001742255787969042,
2175
+ "loss": 4.7436,
2176
+ "step": 305
2177
+ },
2178
+ {
2179
+ "epoch": 0.9611307420494699,
2180
+ "grad_norm": 2.234375,
2181
+ "learning_rate": 0.00017405853173968589,
2182
+ "loss": 4.7237,
2183
+ "step": 306
2184
+ },
2185
+ {
2186
+ "epoch": 0.9642716921868866,
2187
+ "grad_norm": 2.3125,
2188
+ "learning_rate": 0.0001738910257424701,
2189
+ "loss": 4.5708,
2190
+ "step": 307
2191
+ },
2192
+ {
2193
+ "epoch": 0.9674126423243031,
2194
+ "grad_norm": 2.78125,
2195
+ "learning_rate": 0.00017372306184328985,
2196
+ "loss": 4.4765,
2197
+ "step": 308
2198
+ },
2199
+ {
2200
+ "epoch": 0.9705535924617197,
2201
+ "grad_norm": 2.109375,
2202
+ "learning_rate": 0.00017355464108301585,
2203
+ "loss": 4.6697,
2204
+ "step": 309
2205
+ },
2206
+ {
2207
+ "epoch": 0.9736945425991362,
2208
+ "grad_norm": 2.421875,
2209
+ "learning_rate": 0.00017338576450534984,
2210
+ "loss": 4.5376,
2211
+ "step": 310
2212
+ },
2213
+ {
2214
+ "epoch": 0.9768354927365528,
2215
+ "grad_norm": 2.671875,
2216
+ "learning_rate": 0.00017321643315681832,
2217
+ "loss": 4.7185,
2218
+ "step": 311
2219
+ },
2220
+ {
2221
+ "epoch": 0.9799764428739693,
2222
+ "grad_norm": 2.421875,
2223
+ "learning_rate": 0.000173046648086766,
2224
+ "loss": 4.6617,
2225
+ "step": 312
2226
+ },
2227
+ {
2228
+ "epoch": 0.9831173930113859,
2229
+ "grad_norm": 3.1875,
2230
+ "learning_rate": 0.00017287641034734934,
2231
+ "loss": 4.7403,
2232
+ "step": 313
2233
+ },
2234
+ {
2235
+ "epoch": 0.9862583431488026,
2236
+ "grad_norm": 2.21875,
2237
+ "learning_rate": 0.00017270572099352993,
2238
+ "loss": 4.5652,
2239
+ "step": 314
2240
+ },
2241
+ {
2242
+ "epoch": 0.9893992932862191,
2243
+ "grad_norm": 2.765625,
2244
+ "learning_rate": 0.000172534581083068,
2245
+ "loss": 4.5723,
2246
+ "step": 315
2247
+ },
2248
+ {
2249
+ "epoch": 0.9925402434236357,
2250
+ "grad_norm": 2.9375,
2251
+ "learning_rate": 0.00017236299167651593,
2252
+ "loss": 4.6485,
2253
+ "step": 316
2254
+ },
2255
+ {
2256
+ "epoch": 0.9956811935610522,
2257
+ "grad_norm": 3.109375,
2258
+ "learning_rate": 0.0001721909538372116,
2259
+ "loss": 4.5751,
2260
+ "step": 317
2261
+ },
2262
+ {
2263
+ "epoch": 0.9988221436984688,
2264
+ "grad_norm": 3.046875,
2265
+ "learning_rate": 0.0001720184686312718,
2266
+ "loss": 4.5623,
2267
+ "step": 318
2268
+ }
2269
+ ],
2270
+ "logging_steps": 1,
2271
+ "max_steps": 1272,
2272
+ "num_input_tokens_seen": 0,
2273
+ "num_train_epochs": 4,
2274
+ "save_steps": 318,
2275
+ "stateful_callbacks": {
2276
+ "TrainerControl": {
2277
+ "args": {
2278
+ "should_epoch_stop": false,
2279
+ "should_evaluate": false,
2280
+ "should_log": false,
2281
+ "should_save": true,
2282
+ "should_training_stop": false
2283
+ },
2284
+ "attributes": {}
2285
+ }
2286
+ },
2287
+ "total_flos": 2.2355630330845594e+17,
2288
+ "train_batch_size": 1,
2289
+ "trial_name": null,
2290
+ "trial_params": null
2291
+ }
checkpoint-318/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:34c048912f6ba3fdf50f66b1635aa253feb31cfba85c9f47fc5603099baef225
3
+ size 5944
checkpoint-318/vocab.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-636/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ base_model: Qwen/Qwen2-7B
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 0.11.1
checkpoint-636/adapter_config.json ADDED
@@ -0,0 +1,34 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "Qwen/Qwen2-7B",
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": 64,
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
+ "q_proj",
24
+ "v_proj",
25
+ "k_proj",
26
+ "down_proj",
27
+ "gate_proj",
28
+ "o_proj",
29
+ "up_proj"
30
+ ],
31
+ "task_type": "CAUSAL_LM",
32
+ "use_dora": false,
33
+ "use_rslora": false
34
+ }
checkpoint-636/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b07d6ee74007904be8bdfc0276e3e9d743b7720aab9a4391f04959f75190460d
3
+ size 161533584
checkpoint-636/added_tokens.json ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+ {
2
+ "<|endoftext|>": 151643,
3
+ "<|im_end|>": 151645,
4
+ "<|im_start|>": 151644
5
+ }
checkpoint-636/merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-636/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:2c6c59012ea80fa2d5312ce6ffd4d03653dce0d304eb47121ba16c55165d7444
3
+ size 323292010
checkpoint-636/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:65f540726a21b66ac948a449f0493d515b3e0f5fd4c8fa79d8c5609763375c4b
3
+ size 14244
checkpoint-636/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:569f4c805f3e58d4307eff4de10074f081dc248f83cfce3c3df473761292b689
3
+ size 1064
checkpoint-636/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-636/tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-636/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-636/trainer_state.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-636/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:34c048912f6ba3fdf50f66b1635aa253feb31cfba85c9f47fc5603099baef225
3
+ size 5944
checkpoint-636/vocab.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-954/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ base_model: Qwen/Qwen2-7B
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 0.11.1
checkpoint-954/adapter_config.json ADDED
@@ -0,0 +1,34 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "Qwen/Qwen2-7B",
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": 64,
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
+ "q_proj",
24
+ "v_proj",
25
+ "k_proj",
26
+ "down_proj",
27
+ "gate_proj",
28
+ "o_proj",
29
+ "up_proj"
30
+ ],
31
+ "task_type": "CAUSAL_LM",
32
+ "use_dora": false,
33
+ "use_rslora": false
34
+ }
checkpoint-954/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:054c164ed96935e000b99ce00a988bd298fe4270ce2508e6614fb9f549795e7b
3
+ size 161533584
checkpoint-954/added_tokens.json ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+ {
2
+ "<|endoftext|>": 151643,
3
+ "<|im_end|>": 151645,
4
+ "<|im_start|>": 151644
5
+ }