uf-tulu-2-7b-dpo-full
This model is a fine-tuned version of models/tulu-2-7b-uf-dpo on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
- Loss: 0.6557
- Rewards/chosen: -0.2228
- Rewards/rejected: -0.3409
- Rewards/accuracies: 0.7422
- Rewards/margins: 0.1181
- Logps/rejected: -359.4563
- Logps/chosen: -339.0808
- Logits/rejected: -1.0471
- Logits/chosen: -1.0577
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: 4
- total_train_batch_size: 256
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6765 | 0.4184 | 100 | 0.6735 | -0.1002 | -0.1550 | 0.7148 | 0.0548 | -340.8675 | -326.8218 | -1.1563 | -1.1550 |
| 0.6549 | 0.8368 | 200 | 0.6562 | -0.2176 | -0.3342 | 0.7305 | 0.1165 | -358.7881 | -338.5682 | -1.0513 | -1.0615 |
Framework versions
- Transformers 4.44.1
- Pytorch 2.1.2+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1