mistral-7b-dpo-full-sft-wo-medication_qa
This model is a fine-tuned version of Minbyul/mistral-7b-wo-medication_qa-sft on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
- Loss: 0.0756
- Rewards/chosen: -3.7115
- Rewards/rejected: -11.1989
- Rewards/accuracies: 0.9531
- Rewards/margins: 7.4875
- Logps/rejected: -1662.8185
- Logps/chosen: -803.2770
- Logits/rejected: -2.3910
- Logits/chosen: -2.5860
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-07
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Logits/chosen | Logits/rejected | Logps/chosen | Logps/rejected | Validation Loss | Rewards/accuracies | Rewards/chosen | Rewards/margins | Rewards/rejected |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.2799 | 0.31 | 100 | -3.0348 | -3.0868 | -584.1479 | -794.0103 | 0.5261 | 0.75 | -1.5202 | 0.9907 | -2.5108 |
| 0.154 | 0.62 | 200 | -2.6948 | -2.5547 | -742.1359 | -1446.8754 | 0.0923 | 0.9375 | -3.1001 | 5.9394 | -9.0395 |
| 0.0948 | 0.92 | 300 | -2.5877 | -2.3930 | -803.1033 | -1661.4266 | 0.0753 | 0.9531 | -3.7097 | 7.4753 | -11.1850 |
Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.2
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