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--- |
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base_model: HuggingFaceTB/cosmo2-350M-webinst-sc2 |
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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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- trl |
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- dpo |
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- generated_from_trainer |
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datasets: |
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- argilla/dpo-mix-7k |
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model-index: |
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- name: cosmo2-350M-webinst-sc2-dpo-argilla-ep1 |
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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/loubnabnl/huggingface/runs/z5gb262b) |
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# cosmo2-350M-webinst-sc2-dpo-argilla-ep1 |
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This model is a fine-tuned version of [HuggingFaceTB/cosmo2-350M-webinst-sc2](https://huggingface.co./HuggingFaceTB/cosmo2-350M-webinst-sc2) on the argilla/dpo-mix-7k dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6834 |
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- Rewards/chosen: -0.0086 |
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- Rewards/rejected: -0.0304 |
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- Rewards/accuracies: 0.5938 |
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- Rewards/margins: 0.0218 |
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- Logps/rejected: -418.5675 |
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- Logps/chosen: -442.4709 |
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- Logits/rejected: -0.7106 |
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- Logits/chosen: -0.5211 |
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- IFEval prompt loose 17.01 |
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- IFEval prompt strict 14.05 |
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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: 2 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 32 |
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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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- 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 |
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