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Model: open-thoughts/OpenThinker-7B Source: Original Platform
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README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model: Qwen/Qwen2.5-7B-Instruct
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tags:
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- llama-factory
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- full
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- generated_from_trainer
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model-index:
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- name: OpenThinker-7B
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results: []
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datasets:
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- open-thoughts/open-thoughts-114k
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---
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<p align="center">
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<img src="https://huggingface.co/datasets/open-thoughts/open-thoughts-114k/resolve/main/open_thoughts.png" width="50%">
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</p>
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> [!NOTE]
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> We have released a paper for OpenThoughts! See our paper [here](https://arxiv.org/abs/2506.04178).
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# OpenThinker-7B
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This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on the
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[OpenThoughts-114k dataset](https://huggingface.co/datasets/open-thoughts/OpenThoughts-114k) dataset.
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The dataset is derived by distilling DeepSeek-R1 using the [data pipeline available on github](https://github.com/open-thoughts/open-thoughts).
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More info about the dataset can be found on the dataset card at [OpenThoughts-114k dataset](https://huggingface.co/datasets/open-thoughts/open-thoughts-114k).
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This model improves upon the [Bespoke-Stratos-7B model](https://huggingface.co/bespokelabs/Bespoke-Stratos-7B), which used 17k examples ([Bespoke-Stratos-17k dataset](https://huggingface.co/datasets/bespokelabs/Bespoke-Stratos-17k)).
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The numbers reported in the table below are evaluated with our open-source tool [Evalchemy](https://github.com/mlfoundations/Evalchemy).
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| | AIME24 | MATH500 | GPQA-Diamond | LCBv2 Easy | LCBv2 Medium | LCBv2 Hard | LCBv2 All |
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| --------------------------- | -------- | ------- | ------------ | ----------- | ------------- | ----------- | ---------- |
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| OpenThinker-7B | 31.3 | 83.0 | 42.4 | 75.3 | 28.6 | 6.5 | 39.9 |
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| Bespoke-Stratos-7B | 22.7 | 79.6 | 38.9 | 71.4 | 25.2 | 0.8 | 35.8 |
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| DeepSeek-R1-Distill-Qwen-7B | 60 | 88.2 | 46.9 | 79.7 | 45.1 | 14.6 | 50.1 |
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| gpt-4o-0513 | 8.7 | 75.8 | 46.5 | 87.4 | 42.7 | 8.9 | 50.5 |
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| o1-mini | 64 | 85.6 | 60 | 92.8 | 74.7 | 39.8 | 72.8 |
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We are fully open-source. Our [model weights](https://huggingface.co/open-thoughts), [datasets](https://huggingface.co/open-thoughts), [data generation code](https://github.com/open-thoughts/open-thoughts), [evaluation code](https://github.com/mlfoundations/Evalchemy), and [training code](https://github.com/hiyouga/LLaMA-Factory) are all publicly available.
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| | Open Weights | Open Data | Open Code |
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|--|--------------|-----------| --------- |
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|OpenThinker-7B|✅|[✅](https://huggingface.co/datasets/open-thoughts/OpenThoughts-114k)|[✅](https://github.com/open-thoughts/open-thoughts) |
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|Bespoke-Stratos-7B|✅|[✅](https://huggingface.co/datasets/bespokelabs/Bespoke-Stratos-17k)|[✅](https://github.com/bespokelabsai/curator/tree/main/examples/bespoke-stratos-data-generation)|
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|DeepSeek-R1-Distill-Qwen-7B|✅|❌|❌|
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|gpt-4o-0513|❌|❌|❌|❌|
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|o1-mini|❌|❌|❌|❌|
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## Intended uses & limitations
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Apache 2.0 License
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## Training procedure
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We used four 8xH100 nodes to train the model for 20 hours.
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1e-05
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- train_batch_size: 1
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- eval_batch_size: 8
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 32
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- gradient_accumulation_steps: 3
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- total_train_batch_size: 96
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- total_eval_batch_size: 256
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 3.0
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### Framework versions
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- Transformers 4.46.1
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- Pytorch 2.3.0
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- Datasets 3.1.0
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- Tokenizers 0.20.3
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More info can be found in our repository: [https://github.com/open-thoughts/open-thoughts](https://github.com/open-thoughts/open-thoughts).
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# Links
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- 📝 [OpenThoughts Paper](https://arxiv.org/abs/2506.04178)
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- 📊 [Open Thoughts Launch Blog Post](https://www.open-thoughts.ai/blog/launch)
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- 💻 [Open Thoughts GitHub Repository](https://github.com/open-thoughts/open-thoughts)
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- 🧠 [OpenThoughts-114k dataset](https://huggingface.co/datasets/open-thoughts/OpenThoughts-114k)
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- 🤖 [OpenThinker-7B model](https://huggingface.co/open-thoughts/OpenThinker-7B) - this model.
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- 📊 [Bespoke-Stratos Blog Post](https://www.bespokelabs.ai/blog/bespoke-stratos-the-unreasonable-effectiveness-of-reasoning-distillation)
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- 🧠 [Bespoke-Stratos-17k dataset](https://huggingface.co/datasets/bespokelabs/Bespoke-Stratos-17k)
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- 🤖 [Bespoke-Stratos-32B model](https://huggingface.co/bespokelabs/Bespoke-Stratos-32B)
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- 🤖 [Bespoke-Stratos-7B model](https://huggingface.co/bespokelabs/Bespoke-Stratos-7B)
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# Citation
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```
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@misc{guha2025openthoughtsdatarecipesreasoning,
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title={OpenThoughts: Data Recipes for Reasoning Models},
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author={Etash Guha and Ryan Marten and Sedrick Keh and Negin Raoof and Georgios Smyrnis and Hritik Bansal and Marianna Nezhurina and Jean Mercat and Trung Vu and Zayne Sprague and Ashima Suvarna and Benjamin Feuer and Liangyu Chen and Zaid Khan and Eric Frankel and Sachin Grover and Caroline Choi and Niklas Muennighoff and Shiye Su and Wanjia Zhao and John Yang and Shreyas Pimpalgaonkar and Kartik Sharma and Charlie Cheng-Jie Ji and Yichuan Deng and Sarah Pratt and Vivek Ramanujan and Jon Saad-Falcon and Jeffrey Li and Achal Dave and Alon Albalak and Kushal Arora and Blake Wulfe and Chinmay Hegde and Greg Durrett and Sewoong Oh and Mohit Bansal and Saadia Gabriel and Aditya Grover and Kai-Wei Chang and Vaishaal Shankar and Aaron Gokaslan and Mike A. Merrill and Tatsunori Hashimoto and Yejin Choi and Jenia Jitsev and Reinhard Heckel and Maheswaran Sathiamoorthy and Alexandros G. Dimakis and Ludwig Schmidt},
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year={2025},
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eprint={2506.04178},
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archivePrefix={arXiv},
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primaryClass={cs.LG},
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url={https://arxiv.org/abs/2506.04178},
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}
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```
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"train_samples_per_second": 4.686,
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"train_steps_per_second": 0.049
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config.json
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"_name_or_path": "Qwen/Qwen2.5-7B-Instruct",
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"intermediate_size": 18944,
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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_key_value_heads": 4,
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configs.yaml
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assistant_tag: assistant
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bf16: 'True'
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content_tag: value
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cutoff_len: '16384'
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dataset: mlfoundations-dev/stratos_verified_mix
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dataset_dir: ONLINE
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ddp_timeout: '180000000'
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deepspeed: /opt/ml/code/zero3_offload.json
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do_train: 'True'
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enable_liger_kernel: 'False'
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finetuning_type: full
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formatting: sharegpt
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global_batch_size: '96'
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gradient_accumulation_steps: '3'
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hub_model_id: mlfoundations-dev/DCFT-Stratos-Verified-114k-7B-4gpus
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learning_rate: 1e-05
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logging_steps: '1'
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lr_scheduler_type: cosine
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max_samples: '1000000'
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messages: conversations
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model_name_or_path: Qwen/Qwen2.5-7B-Instruct
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num_train_epochs: '3.0'
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output_dir: /opt/ml/model
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overwrite_cache: 'True'
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per_device_train_batch_size: '1'
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plot_loss: 'True'
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preprocessing_num_workers: '16'
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push_to_db: 'True'
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push_to_hub: 'True'
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report_to: wandb
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role_tag: from
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run_name: Stratos-35k-32B-DCFT
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save_steps: '100'
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stage: sft
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template: qwen25
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user_tag: user
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warmup_ratio: '0.1'
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|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151663": {
|
||||
"content": "<|repo_name|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151664": {
|
||||
"content": "<|file_sep|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|object_ref_start|>",
|
||||
"<|object_ref_end|>",
|
||||
"<|box_start|>",
|
||||
"<|box_end|>",
|
||||
"<|quad_start|>",
|
||||
"<|quad_end|>",
|
||||
"<|vision_start|>",
|
||||
"<|vision_end|>",
|
||||
"<|vision_pad|>",
|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"bos_token": null,
|
||||
"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",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|endoftext|>",
|
||||
"errors": "replace",
|
||||
"model_max_length": 131072,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"padding_side": "right",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
8
train_results.json
Normal file
8
train_results.json
Normal file
@@ -0,0 +1,8 @@
|
||||
{
|
||||
"epoch": 2.9991577765300392,
|
||||
"total_flos": 4618853558517760.0,
|
||||
"train_loss": 0.43624040107819445,
|
||||
"train_runtime": 72959.568,
|
||||
"train_samples_per_second": 4.686,
|
||||
"train_steps_per_second": 0.049
|
||||
}
|
||||
3562
trainer_log.jsonl
Normal file
3562
trainer_log.jsonl
Normal file
File diff suppressed because it is too large
Load Diff
24969
trainer_state.json
Normal file
24969
trainer_state.json
Normal file
File diff suppressed because it is too large
Load Diff
3
training_args.bin
Normal file
3
training_args.bin
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:0deb7dbbed94bf8fee369a6cd469db6e7fb6d94e0c196c1cd2eeeef856361520
|
||||
size 7352
|
||||
BIN
training_loss.png
Normal file
BIN
training_loss.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 37 KiB |
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user