HuggingFaceH4/ultrafeedback_binarized
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How to use EllieS/zephyr-7b-dpo-lora-pubmedqa-selfgen-ultrafeedback-com with PEFT:
from peft import PeftModel
from transformers import AutoModelForCausalLM
base_model = AutoModelForCausalLM.from_pretrained("alignment-handbook/zephyr-7b-sft-full")
model = PeftModel.from_pretrained(base_model, "EllieS/zephyr-7b-dpo-lora-pubmedqa-selfgen-ultrafeedback-com")This model is a fine-tuned version of EllieS/zephyr-7b-dpo-lora-pubmedqa-selfgen-complete on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.5526 | 0.39 | 3000 | 0.6013 | -0.1508 | -0.4054 | 0.7040 | 0.2546 | -291.8378 | -299.8007 | -2.5651 | -2.5923 |
| 0.5814 | 0.79 | 6000 | 0.5867 | -0.2418 | -0.5459 | 0.7080 | 0.3040 | -305.8824 | -308.9029 | -2.5202 | -2.5505 |
Base model
mistralai/Mistral-7B-v0.1