zephyr-7b-dpo-full-ultrabin-2
This model is a fine-tuned version of alignment-handbook/zephyr-7b-sft-full on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
- Loss: 0.5012
- Rewards/chosen: -1.0205
- Rewards/rejected: -1.9949
- Rewards/accuracies: 0.7734
- Rewards/margins: 0.9744
- Logps/rejected: -462.1516
- Logps/chosen: -364.6655
- Logits/rejected: 0.2960
- Logits/chosen: -0.5539
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: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- total_eval_batch_size: 64
- 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 | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.5737 | 0.2092 | 100 | 0.5691 | -0.6944 | -1.2209 | 0.7227 | 0.5264 | -384.7459 | -332.0635 | -1.3889 | -1.5290 |
| 0.5456 | 0.4184 | 200 | 0.5217 | -0.8959 | -1.6744 | 0.7812 | 0.7785 | -430.1032 | -352.2071 | -0.6808 | -1.2567 |
| 0.4938 | 0.6276 | 300 | 0.5073 | -0.9394 | -1.8266 | 0.7695 | 0.8872 | -445.3213 | -356.5596 | -0.2199 | -0.9537 |
| 0.5014 | 0.8368 | 400 | 0.5015 | -1.0166 | -1.9608 | 0.7656 | 0.9442 | -458.7432 | -364.2830 | 0.1887 | -0.6221 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1