Upload folder using huggingface_hub
Browse files- .gitattributes +6 -34
- README.md +65 -0
- added_tokens.json +24 -0
- all_results.json +8 -0
- config.json +29 -0
- generation_config.json +14 -0
- merges.txt +0 -0
- model-00001-of-00004.safetensors +3 -0
- model-00002-of-00004.safetensors +3 -0
- model-00003-of-00004.safetensors +3 -0
- model-00004-of-00004.safetensors +3 -0
- model.safetensors.index.json +346 -0
- special_tokens_map.json +25 -0
- tokenizer.json +3 -0
- tokenizer_config.json +208 -0
- train_results.json +8 -0
- trainer_state.json +590 -0
- training_args.bin +3 -0
- vocab.json +0 -0
.gitattributes
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training_args.bin filter=lfs diff=lfs merge=lfs -text
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model-00001-of-00004.safetensors filter=lfs diff=lfs merge=lfs -text
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model-00004-of-00004.safetensors filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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library_name: transformers
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tags:
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- generated_from_trainer
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- open-r1
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licence: license
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---
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# Model Card for None
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This model is a fine-tuned version of [None](https://huggingface.co/None).
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It has been trained using [TRL](https://github.com/huggingface/trl).
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## Quick start
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```python
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from transformers import pipeline
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question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
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generator = pipeline("text-generation", model="None", device="cuda")
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output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
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print(output["generated_text"])
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```
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## Training procedure
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/sishuzheng/huggingface/runs/gl2cndfa)
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This model was trained with GRPO, a method introduced in [DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models](https://huggingface.co/papers/2402.03300).
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### Framework versions
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| 33 |
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- TRL: 0.14.0
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- Transformers: 4.49.0
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- Pytorch: 2.5.1
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- Datasets: 3.3.2
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- Tokenizers: 0.21.0
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| 39 |
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## Citations
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Cite GRPO as:
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| 43 |
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```bibtex
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@article{zhihong2024deepseekmath,
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title = {{DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models}},
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author = {Zhihong Shao and Peiyi Wang and Qihao Zhu and Runxin Xu and Junxiao Song and Mingchuan Zhang and Y. K. Li and Y. Wu and Daya Guo},
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year = 2024,
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eprint = {arXiv:2402.03300},
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}
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```
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Cite TRL as:
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| 55 |
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```bibtex
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@misc{vonwerra2022trl,
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| 58 |
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title = {{TRL: Transformer Reinforcement Learning}},
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| 59 |
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author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec},
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| 60 |
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year = 2020,
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| 61 |
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journal = {GitHub repository},
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| 62 |
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publisher = {GitHub},
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| 63 |
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howpublished = {\url{https://github.com/huggingface/trl}}
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| 64 |
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}
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| 65 |
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```
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added_tokens.json
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{
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"</tool_call>": 151658,
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"<|endoftext|>": 151643,
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}
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all_results.json
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{
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"total_flos": 0.0,
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"train_loss": 0.004093525352080614,
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"train_runtime": 40685.3767,
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"train_samples": 10000,
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"train_samples_per_second": 0.492,
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"train_steps_per_second": 0.004
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}
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config.json
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{
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"_name_or_path": "/mnt/public/share/users/sishuzheng/models/qwen2.5-7b-instruct",
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| 3 |
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"architectures": [
|
| 4 |
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"Qwen2ForCausalLM"
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],
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| 6 |
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"attention_dropout": 0.0,
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"hidden_act": "silu",
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"max_position_embeddings": 32768,
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"max_window_layers": 28,
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"model_type": "qwen2",
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"num_attention_heads": 28,
|
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"num_hidden_layers": 28,
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"rope_scaling": null,
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|
| 24 |
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"torch_dtype": "bfloat16",
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| 25 |
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"transformers_version": "4.49.0",
|
| 26 |
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"use_cache": true,
|
| 27 |
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"use_sliding_window": false,
|
| 28 |
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"vocab_size": 152064
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}
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generation_config.json
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{
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"do_sample": true,
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"eos_token_id": [
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151645,
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"repetition_penalty": 1.05,
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"temperature": 0.7,
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"top_k": 20,
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| 12 |
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"top_p": 0.8,
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"transformers_version": "4.49.0"
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}
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merges.txt
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model-00001-of-00004.safetensors
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model-00002-of-00004.safetensors
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model-00003-of-00004.safetensors
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model-00004-of-00004.safetensors
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model.safetensors.index.json
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| 317 |
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|
| 318 |
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|
| 319 |
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|
| 320 |
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|
| 321 |
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|
| 322 |
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|
| 323 |
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|
| 324 |
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|
| 325 |
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"model.layers.8.self_attn.k_proj.bias": "model-00001-of-00004.safetensors",
|
| 326 |
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|
| 327 |
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|
| 328 |
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|
| 329 |
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"model.layers.8.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
|
| 330 |
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"model.layers.8.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
|
| 331 |
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"model.layers.8.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
|
| 332 |
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"model.layers.9.input_layernorm.weight": "model-00002-of-00004.safetensors",
|
| 333 |
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|
| 334 |
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"model.layers.9.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
|
| 335 |
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|
| 336 |
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"model.layers.9.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
|
| 337 |
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|
| 338 |
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|
| 339 |
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|
| 340 |
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|
| 341 |
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|
| 342 |
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"model.layers.9.self_attn.v_proj.bias": "model-00002-of-00004.safetensors",
|
| 343 |
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|
| 344 |
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"model.norm.weight": "model-00003-of-00004.safetensors"
|
| 345 |
+
}
|
| 346 |
+
}
|
special_tokens_map.json
ADDED
|
@@ -0,0 +1,25 @@
|
|
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|
|
|
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|
|
|
|
|
|
|
|
|
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|
|
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|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"additional_special_tokens": [
|
| 3 |
+
"<|im_start|>",
|
| 4 |
+
"<|im_end|>",
|
| 5 |
+
"<|object_ref_start|>",
|
| 6 |
+
"<|object_ref_end|>",
|
| 7 |
+
"<|box_start|>",
|
| 8 |
+
"<|box_end|>",
|
| 9 |
+
"<|quad_start|>",
|
| 10 |
+
"<|quad_end|>",
|
| 11 |
+
"<|vision_start|>",
|
| 12 |
+
"<|vision_end|>",
|
| 13 |
+
"<|vision_pad|>",
|
| 14 |
+
"<|image_pad|>",
|
| 15 |
+
"<|video_pad|>"
|
| 16 |
+
],
|
| 17 |
+
"eos_token": {
|
| 18 |
+
"content": "<|im_end|>",
|
| 19 |
+
"lstrip": false,
|
| 20 |
+
"normalized": false,
|
| 21 |
+
"rstrip": false,
|
| 22 |
+
"single_word": false
|
| 23 |
+
},
|
| 24 |
+
"pad_token": "<|im_end|>"
|
| 25 |
+
}
|
tokenizer.json
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:63a2951d5edfa5cc0a2346ef872f8c77a2920274cfc3b503b04e3799104dee80
|
| 3 |
+
size 11422060
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,208 @@
|
|
|
|
|
|
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|
|
|
|
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|
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|
|
|
|
|
|
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|
|
|
|
|
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|
|
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|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_bos_token": false,
|
| 3 |
+
"add_prefix_space": false,
|
| 4 |
+
"added_tokens_decoder": {
|
| 5 |
+
"151643": {
|
| 6 |
+
"content": "<|endoftext|>",
|
| 7 |
+
"lstrip": false,
|
| 8 |
+
"normalized": false,
|
| 9 |
+
"rstrip": false,
|
| 10 |
+
"single_word": false,
|
| 11 |
+
"special": true
|
| 12 |
+
},
|
| 13 |
+
"151644": {
|
| 14 |
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"content": "<|im_start|>",
|
| 15 |
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"lstrip": false,
|
| 16 |
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"normalized": false,
|
| 17 |
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"rstrip": false,
|
| 18 |
+
"single_word": false,
|
| 19 |
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"special": true
|
| 20 |
+
},
|
| 21 |
+
"151645": {
|
| 22 |
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"content": "<|im_end|>",
|
| 23 |
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"lstrip": false,
|
| 24 |
+
"normalized": false,
|
| 25 |
+
"rstrip": false,
|
| 26 |
+
"single_word": false,
|
| 27 |
+
"special": true
|
| 28 |
+
},
|
| 29 |
+
"151646": {
|
| 30 |
+
"content": "<|object_ref_start|>",
|
| 31 |
+
"lstrip": false,
|
| 32 |
+
"normalized": false,
|
| 33 |
+
"rstrip": false,
|
| 34 |
+
"single_word": false,
|
| 35 |
+
"special": true
|
| 36 |
+
},
|
| 37 |
+
"151647": {
|
| 38 |
+
"content": "<|object_ref_end|>",
|
| 39 |
+
"lstrip": false,
|
| 40 |
+
"normalized": false,
|
| 41 |
+
"rstrip": false,
|
| 42 |
+
"single_word": false,
|
| 43 |
+
"special": true
|
| 44 |
+
},
|
| 45 |
+
"151648": {
|
| 46 |
+
"content": "<|box_start|>",
|
| 47 |
+
"lstrip": false,
|
| 48 |
+
"normalized": false,
|
| 49 |
+
"rstrip": false,
|
| 50 |
+
"single_word": false,
|
| 51 |
+
"special": true
|
| 52 |
+
},
|
| 53 |
+
"151649": {
|
| 54 |
+
"content": "<|box_end|>",
|
| 55 |
+
"lstrip": false,
|
| 56 |
+
"normalized": false,
|
| 57 |
+
"rstrip": false,
|
| 58 |
+
"single_word": false,
|
| 59 |
+
"special": true
|
| 60 |
+
},
|
| 61 |
+
"151650": {
|
| 62 |
+
"content": "<|quad_start|>",
|
| 63 |
+
"lstrip": false,
|
| 64 |
+
"normalized": false,
|
| 65 |
+
"rstrip": false,
|
| 66 |
+
"single_word": false,
|
| 67 |
+
"special": true
|
| 68 |
+
},
|
| 69 |
+
"151651": {
|
| 70 |
+
"content": "<|quad_end|>",
|
| 71 |
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"lstrip": false,
|
| 72 |
+
"normalized": false,
|
| 73 |
+
"rstrip": false,
|
| 74 |
+
"single_word": false,
|
| 75 |
+
"special": true
|
| 76 |
+
},
|
| 77 |
+
"151652": {
|
| 78 |
+
"content": "<|vision_start|>",
|
| 79 |
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"lstrip": false,
|
| 80 |
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"normalized": false,
|
| 81 |
+
"rstrip": false,
|
| 82 |
+
"single_word": false,
|
| 83 |
+
"special": true
|
| 84 |
+
},
|
| 85 |
+
"151653": {
|
| 86 |
+
"content": "<|vision_end|>",
|
| 87 |
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"lstrip": false,
|
| 88 |
+
"normalized": false,
|
| 89 |
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"rstrip": false,
|
| 90 |
+
"single_word": false,
|
| 91 |
+
"special": true
|
| 92 |
+
},
|
| 93 |
+
"151654": {
|
| 94 |
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"content": "<|vision_pad|>",
|
| 95 |
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"lstrip": false,
|
| 96 |
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"normalized": false,
|
| 97 |
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"rstrip": false,
|
| 98 |
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"single_word": false,
|
| 99 |
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"special": true
|
| 100 |
+
},
|
| 101 |
+
"151655": {
|
| 102 |
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"content": "<|image_pad|>",
|
| 103 |
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"lstrip": false,
|
| 104 |
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"normalized": false,
|
| 105 |
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"rstrip": false,
|
| 106 |
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"single_word": false,
|
| 107 |
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"special": true
|
| 108 |
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},
|
| 109 |
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"151656": {
|
| 110 |
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"content": "<|video_pad|>",
|
| 111 |
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|
| 112 |
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"normalized": false,
|
| 113 |
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"rstrip": false,
|
| 114 |
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"single_word": false,
|
| 115 |
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"special": true
|
| 116 |
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},
|
| 117 |
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"151657": {
|
| 118 |
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"content": "<tool_call>",
|
| 119 |
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"lstrip": false,
|
| 120 |
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"normalized": false,
|
| 121 |
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"rstrip": false,
|
| 122 |
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"single_word": false,
|
| 123 |
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"special": false
|
| 124 |
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},
|
| 125 |
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"151658": {
|
| 126 |
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"content": "</tool_call>",
|
| 127 |
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"lstrip": false,
|
| 128 |
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"normalized": false,
|
| 129 |
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"rstrip": false,
|
| 130 |
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"single_word": false,
|
| 131 |
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"special": false
|
| 132 |
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},
|
| 133 |
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"151659": {
|
| 134 |
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"content": "<|fim_prefix|>",
|
| 135 |
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|
| 136 |
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"normalized": false,
|
| 137 |
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|
| 138 |
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"single_word": false,
|
| 139 |
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"special": false
|
| 140 |
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},
|
| 141 |
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"151660": {
|
| 142 |
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"content": "<|fim_middle|>",
|
| 143 |
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|
| 144 |
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"normalized": false,
|
| 145 |
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|
| 146 |
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"single_word": false,
|
| 147 |
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"special": false
|
| 148 |
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},
|
| 149 |
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"151661": {
|
| 150 |
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"content": "<|fim_suffix|>",
|
| 151 |
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|
| 152 |
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|
| 153 |
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|
| 154 |
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|
| 155 |
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|
| 156 |
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|
| 157 |
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"151662": {
|
| 158 |
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"content": "<|fim_pad|>",
|
| 159 |
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|
| 160 |
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|
| 161 |
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|
| 162 |
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"single_word": false,
|
| 163 |
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"special": false
|
| 164 |
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},
|
| 165 |
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"151663": {
|
| 166 |
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"content": "<|repo_name|>",
|
| 167 |
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|
| 168 |
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|
| 169 |
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"rstrip": false,
|
| 170 |
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"single_word": false,
|
| 171 |
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"special": false
|
| 172 |
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},
|
| 173 |
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"151664": {
|
| 174 |
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"content": "<|file_sep|>",
|
| 175 |
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|
| 176 |
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|
| 177 |
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|
| 178 |
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|
| 179 |
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"special": false
|
| 180 |
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}
|
| 181 |
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},
|
| 182 |
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"additional_special_tokens": [
|
| 183 |
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|
| 184 |
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|
| 185 |
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|
| 186 |
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|
| 187 |
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|
| 188 |
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|
| 189 |
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|
| 190 |
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|
| 191 |
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|
| 192 |
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|
| 193 |
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|
| 194 |
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|
| 195 |
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|
| 196 |
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|
| 197 |
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|
| 198 |
+
"chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n {%- else %}\n {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}\n {%- endif %}\n {{- \"\\n\\n# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n {%- if messages[0]['role'] == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n {%- else %}\n {{- '<|im_start|>system\\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {{- '<|im_start|>' + message.role }}\n {%- if message.content %}\n {{- '\\n' + message.content }}\n {%- endif %}\n {%- for tool_call in message.tool_calls %}\n {%- if tool_call.function is defined %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '\\n<tool_call>\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- '}\\n</tool_call>' }}\n {%- endfor %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {{- message.content }}\n {{- '\\n</tool_response>' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n",
|
| 199 |
+
"clean_up_tokenization_spaces": false,
|
| 200 |
+
"eos_token": "<|im_end|>",
|
| 201 |
+
"errors": "replace",
|
| 202 |
+
"extra_special_tokens": {},
|
| 203 |
+
"model_max_length": 131072,
|
| 204 |
+
"pad_token": "<|im_end|>",
|
| 205 |
+
"split_special_tokens": false,
|
| 206 |
+
"tokenizer_class": "Qwen2Tokenizer",
|
| 207 |
+
"unk_token": null
|
| 208 |
+
}
|
train_results.json
ADDED
|
@@ -0,0 +1,8 @@
|
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|
| 1 |
+
{
|
| 2 |
+
"total_flos": 0.0,
|
| 3 |
+
"train_loss": 0.004093525352080614,
|
| 4 |
+
"train_runtime": 40685.3767,
|
| 5 |
+
"train_samples": 10000,
|
| 6 |
+
"train_samples_per_second": 0.492,
|
| 7 |
+
"train_steps_per_second": 0.004
|
| 8 |
+
}
|
trainer_state.json
ADDED
|
@@ -0,0 +1,590 @@
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|
|
| 1 |
+
{
|
| 2 |
+
"best_metric": null,
|
| 3 |
+
"best_model_checkpoint": null,
|
| 4 |
+
"epoch": 1.9846153846153847,
|
| 5 |
+
"eval_steps": 500,
|
| 6 |
+
"global_step": 178,
|
| 7 |
+
"is_hyper_param_search": false,
|
| 8 |
+
"is_local_process_zero": true,
|
| 9 |
+
"is_world_process_zero": true,
|
| 10 |
+
"log_history": [
|
| 11 |
+
{
|
| 12 |
+
"completion_length": 198.35713958740234,
|
| 13 |
+
"epoch": 0.011188811188811189,
|
| 14 |
+
"grad_norm": 2.505012035369873,
|
| 15 |
+
"kl": 0.0,
|
| 16 |
+
"learning_rate": 5.555555555555555e-08,
|
| 17 |
+
"loss": 0.0,
|
| 18 |
+
"reward": 1.5765306055545807,
|
| 19 |
+
"reward_std": 0.5201284289360046,
|
| 20 |
+
"rewards/accuracy_reward": 0.06377550784964114,
|
| 21 |
+
"rewards/format_reward": 0.7499999776482582,
|
| 22 |
+
"rewards/influence_reward": 0.04464285587891936,
|
| 23 |
+
"rewards/len_reward": 0.7181122228503227,
|
| 24 |
+
"step": 1
|
| 25 |
+
},
|
| 26 |
+
{
|
| 27 |
+
"completion_length": 200.2965521812439,
|
| 28 |
+
"epoch": 0.055944055944055944,
|
| 29 |
+
"grad_norm": 2.8937346935272217,
|
| 30 |
+
"kl": 0.0004087686538696289,
|
| 31 |
+
"learning_rate": 2.7777777777777776e-07,
|
| 32 |
+
"loss": 0.0,
|
| 33 |
+
"reward": 1.559630073606968,
|
| 34 |
+
"reward_std": 0.4927491685375571,
|
| 35 |
+
"rewards/accuracy_reward": 0.05516581577830948,
|
| 36 |
+
"rewards/format_reward": 0.7930484488606453,
|
| 37 |
+
"rewards/influence_reward": 0.060267855995334685,
|
| 38 |
+
"rewards/len_reward": 0.651147942058742,
|
| 39 |
+
"step": 5
|
| 40 |
+
},
|
| 41 |
+
{
|
| 42 |
+
"completion_length": 195.26198539733886,
|
| 43 |
+
"epoch": 0.11188811188811189,
|
| 44 |
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"grad_norm": 1.9461793899536133,
|
| 45 |
+
"kl": 0.0036970138549804687,
|
| 46 |
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"learning_rate": 5.555555555555555e-07,
|
| 47 |
+
"loss": 0.0002,
|
| 48 |
+
"reward": 1.6966836541891097,
|
| 49 |
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"reward_std": 0.4601309224963188,
|
| 50 |
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"rewards/accuracy_reward": 0.06887754972558469,
|
| 51 |
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"rewards/format_reward": 0.8744897767901421,
|
| 52 |
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"rewards/influence_reward": 0.07882652895059436,
|
| 53 |
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"rewards/len_reward": 0.6744897827506066,
|
| 54 |
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"step": 10
|
| 55 |
+
},
|
| 56 |
+
{
|
| 57 |
+
"completion_length": 192.52117080688475,
|
| 58 |
+
"epoch": 0.16783216783216784,
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