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--- |
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license: apache-2.0 |
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library_name: peft |
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tags: |
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- alignment-handbook |
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- trl |
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- dpo |
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- generated_from_trainer |
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base_model: mistralai/Mistral-7B-Instruct-v0.2 |
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datasets: |
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- nthakur/multilingual-truthy-v0.1-dpo-pairs |
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- nthakur/multilingual-orca-dpo-pairs |
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- nthakur/multilingual-mistral-neg-orca-dpo-pairs |
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model-index: |
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- name: mistral-7b-instruct-v0.2-dpo-multilingual-mix-1st-apr-final |
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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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# mistral-7b-instruct-v0.2-dpo-multilingual-mix-1st-apr-final |
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This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the nthakur/multilingual-truthy-v0.1-dpo-pairs, the nthakur/multilingual-orca-dpo-pairs and the nthakur/multilingual-mistral-neg-orca-dpo-pairs datasets. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0524 |
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- Rewards/chosen: -0.1806 |
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- Rewards/rejected: -11.0616 |
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- Rewards/accuracies: 0.9918 |
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- Rewards/margins: 10.8811 |
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- Logps/rejected: -1280.7075 |
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- Logps/chosen: -363.8373 |
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- Logits/rejected: -0.2239 |
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- Logits/chosen: -0.5036 |
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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: 5e-06 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 4 |
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- total_train_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: 1 |
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### Training results |
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### Framework versions |
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- PEFT 0.7.1 |
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- Transformers 4.39.0.dev0 |
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- Pytorch 2.2.2 |
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- Datasets 2.14.6 |
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- Tokenizers 0.15.2 |
