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--- |
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base_model: deepseek-ai/deepseek-math-7b-base |
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datasets: |
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- zfz1/my_preference_gsm8k_deepseek |
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library_name: peft |
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license: other |
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tags: |
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- alignment-handbook |
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- trl |
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- orpo |
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- generated_from_trainer |
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model-index: |
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- name: deepseek-8b-orpo-lora |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/thuzfz1/huggingface/runs/zs68qfsi) |
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# deepseek-8b-orpo-lora |
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This model is a fine-tuned version of [deepseek-ai/deepseek-math-7b-base](https://huggingface.co/deepseek-ai/deepseek-math-7b-base) on the zfz1/my_preference_gsm8k_deepseek dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1456 |
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- Rewards/chosen: -0.0726 |
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- Rewards/rejected: -0.0757 |
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- Rewards/accuracies: 0.5647 |
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- Rewards/margins: 0.0031 |
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- Logps/rejected: -0.7569 |
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- Logps/chosen: -0.7262 |
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- Logits/rejected: 30.3288 |
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- Logits/chosen: 30.4427 |
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- Nll Loss: 1.0719 |
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- Log Odds Ratio: -0.6909 |
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- Log Odds Chosen: 0.0553 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 3e-06 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 43 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 2 |
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### Training results |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.42.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
