EllieS/pubmedqa_dpo_selfgen_data
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How to use EllieS/zephyr-7b-dpo-selfgen 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-selfgen")This model is a fine-tuned version of EllieS/zephyr-7b-sft-qlora on the EllieS/pubmedqa_dpo_selfgen_data 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 | Logits/chosen | Logits/rejected | Logps/chosen | Logps/rejected | Validation Loss | Rewards/accuracies | Rewards/chosen | Rewards/margins | Rewards/rejected |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.0241 | 0.42 | 7000 | -2.8328 | -2.8312 | -143.5124 | -856.1008 | 0.0101 | 1.0 | -0.7644 | 7.3411 | -8.1055 |
| 0.0001 | 0.83 | 14000 | -2.3450 | -1.9435 | -714.5292 | -1741.5647 | 0.0002 | 1.0 | -6.4745 | 10.4856 | -16.9602 |
| 0.0003 | 1.25 | 21000 | -2.4293 | -2.0264 | -695.5377 | -1973.5151 | 0.0001 | 1.0 | -6.2846 | 12.9950 | -19.2797 |
| 0.0 | 1.67 | 28000 | -2.5393 | -2.1793 | -619.2334 | -1821.8682 | 0.0001 | 1.0 | -5.5216 | 12.2416 | -17.7632 |
| 0.0001 | 2.09 | 35000 | -2.4633 | -1.9800 | -817.4478 | -2071.8862 | 0.0000 | 1.0 | -7.5037 | 12.7596 | -20.2634 |
| 0.0 | 2.5 | 42000 | -2.4883 | -2.0593 | -730.7642 | -2000.8484 | 0.0000 | 1.0 | -6.6369 | 12.9161 | -19.5530 |
| 0.0001 | 2.92 | 49000 | -2.4895 | -2.0591 | -732.9475 | -1999.9326 | 0.0000 | 1.0 | -6.6587 | 12.8851 | -19.5438 |
Base model
mistralai/Mistral-7B-v0.1