selfbiorag-7b-dpo-full-sft-wo-medication_qa
This model is a fine-tuned version of Minbyul/selfbiorag-7b-wo-medication_qa-sft on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
- Loss: 0.2759
- Rewards/chosen: -1.2305
- Rewards/rejected: -7.1000
- Rewards/accuracies: 0.8920
- Rewards/margins: 5.8695
- Logps/rejected: -1442.5582
- Logps/chosen: -679.8936
- Logits/rejected: -0.3285
- Logits/chosen: -0.3524
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-06
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.2249 | 0.32 | 100 | -0.1107 | -0.0290 | -650.2339 | -1190.2701 | 0.3821 | 0.8551 | -0.9339 | 3.6432 | -4.5771 |
| 0.1549 | 0.65 | 200 | -0.3180 | -0.3222 | -652.9113 | -1308.4048 | 0.2709 | 0.8977 | -0.9607 | 4.7978 | -5.7585 |
| 0.0946 | 0.97 | 300 | -0.3523 | -0.3283 | -679.6155 | -1442.4718 | 0.2756 | 0.8920 | -1.2277 | 5.8714 | -7.0991 |
Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.2