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---
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license: Apache License 2.0
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#model-type:
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##如 gpt、phi、llama、chatglm、baichuan 等
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#- gpt
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#domain:
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##如 nlp、cv、audio、multi-modal
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#- nlp
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#language:
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##语言代码列表 https://help.aliyun.com/document_detail/215387.html?spm=a2c4g.11186623.0.0.9f8d7467kni6Aa
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#- cn
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#metrics:
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##如 CIDEr、Blue、ROUGE 等
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#- CIDEr
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#tags:
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##各种自定义,包括 pretrained、fine-tuned、instruction-tuned、RL-tuned 等训练方法和其他
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#- pretrained
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#tools:
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##如 vllm、fastchat、llamacpp、AdaSeq 等
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#- vllm
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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: OpenThinker2-7B
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results: []
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datasets:
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- open-thoughts/OpenThoughts2-1M
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---
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### 当前模型的贡献者未提供更加详细的模型介绍。模型文件和权重,可浏览“模型文件”页面获取。
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#### 您可以通过如下git clone命令,或者ModelScope SDK来下载模型
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SDK下载
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```bash
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#安装ModelScope
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pip install modelscope
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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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# OpenThinker2-7B
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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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[OpenThoughts2-1M](https://huggingface.co/datasets/open-thoughts/OpenThoughts2-1M) dataset.
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The [OpenThinker2-7B](https://huggingface.co/open-thoughts/OpenThinker2-7B) model is the top 7B open-data reasoning model. It delivers performance comparable to state of the art 7B models like [DeepSeek-R1-Distill-7B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B) across a suite of tasks.
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This model improves upon our previous [OpenThinker-7B](https://huggingface.co/open-thoughts/OpenThinker-7B) model, which was trained on 114k examples from [OpenThoughts-114k](https://huggingface.co/datasets/open-thoughts/open-thoughts-114k).
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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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| Model | Data | AIME24 | AIME25 | AMC23 | MATH500 | GPQA-D | LCBv2 |
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| --------------------------------------------------------------------------------------------- | ---- | ------ | ------ | ----- | ------- | ------ | ----------- |
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| [OpenThinker2-7B](https://huggingface.co/open-thoughts/OpenThinker2-7B) | ✅ | 50.0 | 33.3 | 89.5 | 88.4 | 49.3 | 55.6 |
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| [OpenThinker-7B](https://huggingface.co/open-thoughts/OpenThinker-7B) | ✅ | 31.3 | 23.3 | 74.5 | 83.2 | 42.9 | 38.0 |
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| [DeepSeek-R1-Distill-Qwen-7B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B) | ❌ | 57.3 | 33.3 | 92.0 | 89.6 | 47.3 | 48.4 |
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| [OlympicCoder-7B](https://huggingface.co/open-r1/OlympicCoder-7B) | ✅ | 20.7 | 15.3 | 63.0 | 74.8 | 25.3 | 55.4 |
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| [OpenR1-Qwen-7B](https://huggingface.co/open-r1/OpenR1-Qwen-7B) | ✅ | 48.7 | 34.7 | 88.5 | 87.8 | 21.2 | 9.5<br><br> |
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## Data
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This model was trained on the [OpenThoughts2-1M](https://huggingface.co/datasets/open-thoughts/OpenThoughts2-1M) dataset.
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The [OpenThoughts2-1M](https://huggingface.co/datasets/open-thoughts/OpenThoughts2-1M) dataset was constructed by augmenting [OpenThoughts-114k](https://huggingface.co/datasets/open-thoughts/open-thoughts-114k) with existing datasets like [OpenR1](https://huggingface.co/open-r1), as well as additional math and code reasoning data.
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We generate the additional math and code data by ablating over 26 different question generation methodologies and sampling from the highest performing ones.
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See the [OpenThoughts2-1M](https://huggingface.co/datasets/open-thoughts/OpenThoughts2-1M) dataset page or our [blog post](https://www.open-thoughts.ai/blog/thinkagain) for additional information.
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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 32 8xA100 nodes to train the model for 36 hours.
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 8e-05
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 256
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 512
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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: 5.0
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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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# Citation
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```
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```python
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#SDK模型下载
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from modelscope import snapshot_download
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model_dir = snapshot_download('open-thoughts/OpenThinker2-7B')
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```
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Git下载
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```
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#Git模型下载
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git clone https://www.modelscope.cn/open-thoughts/OpenThinker2-7B.git
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@misc{openthoughts,
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author = {Team, OpenThoughts},
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month = jan,
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title = {{Open Thoughts}},
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howpublished = {https://open-thoughts.ai},
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year = {2025}
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}
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```
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<p style="color: lightgrey;">如果您是本模型的贡献者,我们邀请您根据<a href="https://modelscope.cn/docs/ModelScope%E6%A8%A1%E5%9E%8B%E6%8E%A5%E5%85%A5%E6%B5%81%E7%A8%8B%E6%A6%82%E8%A7%88" style="color: lightgrey; text-decoration: underline;">模型贡献文档</a>,及时完善模型卡片内容。</p>
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# Links
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- 📊 [OpenThoughts2 and OpenThinker2 Blog Post](https://www.open-thoughts.ai/blog/thinkagain)
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- 💻 [Open Thoughts GitHub Repository](https://github.com/open-thoughts/open-thoughts)
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- 🧠 [OpenThoughts2-1M dataset](https://huggingface.co/datasets/open-thoughts/OpenThoughts2-1M)
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- 🤖 [OpenThinker2-7B model](https://huggingface.co/open-thoughts/OpenThinker2-7B) - this model.
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- 🤖 [OpenThinker2-32B model](https://huggingface.co/open-thoughts/OpenThinker2-32B)
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{
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"epoch": 5.0,
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"total_flos": 4.771898416222647e+19,
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"train_loss": 0.3984597723861392,
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"train_runtime": 127190.7012,
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"train_samples_per_second": 13.986,
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"train_steps_per_second": 0.027
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}
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config.json
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{
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"_name_or_path": "Qwen/Qwen2.5-7B-Instruct",
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"architectures": [
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"Qwen2ForCausalLM"
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"attention_dropout": 0.0,
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"bos_token_id": 151643,
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"eos_token_id": 151645,
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"hidden_act": "silu",
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"hidden_size": 3584,
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"initializer_range": 0.02,
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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_hidden_layers": 28,
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"num_key_value_heads": 4,
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"rms_norm_eps": 1e-06,
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"rope_scaling": null,
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"rope_theta": 1000000.0,
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"sliding_window": null,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.46.1",
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"use_cache": false,
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"use_sliding_window": false,
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"vocab_size": 152064
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}
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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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dataloader_num_workers: '4'
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dataloader_persistent_workers: 'True'
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dataloader_pin_memory: 'True'
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dataset: mlfoundations-dev/hero_run_2_fix_conversations
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dataset_dir: ONLINE
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ddp_timeout: '180000000'
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deepspeed: /opt/ml/code/zero3.json
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do_train: 'True'
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enable_liger_kernel: 'True'
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finetuning_type: full
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formatting: sharegpt
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global_batch_size: '512'
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gradient_accumulation_steps: '2'
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hub_model_id: mlfoundations-dev/hero_run_2_fix_conversations
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learning_rate: 8e-05
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logging_steps: '1'
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lr_scheduler_type: cosine
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messages: conversations
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model_name_or_path: Qwen/Qwen2.5-7B-Instruct
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neat_packing: 'True'
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num_train_epochs: '5.0'
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output_dir: /opt/ml/model
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overwrite_cache: 'True'
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packing: '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: hero_run_2_fix_conversations
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save_strategy: epoch
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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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{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
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"top_p": 0.8,
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"transformers_version": "4.46.1"
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|
||||
"<|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": 5.0,
|
||||
"total_flos": 4.771898416222647e+19,
|
||||
"train_loss": 0.3984597723861392,
|
||||
"train_runtime": 127190.7012,
|
||||
"train_samples_per_second": 13.986,
|
||||
"train_steps_per_second": 0.027
|
||||
}
|
||||
3476
trainer_log.jsonl
Normal file
3476
trainer_log.jsonl
Normal file
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Load Diff
24367
trainer_state.json
Normal file
24367
trainer_state.json
Normal file
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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 sha256:6cf0fa0c9fde140b65e7ca78f6ab81b8d3284cf8c74e6e14e2760abc143ba0cd
|
||||
size 129
|
||||
BIN
training_loss.png
Normal file
BIN
training_loss.png
Normal file
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|
After Width: | Height: | Size: 27 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