ultrafeedback-binarized-tulu-2-7b-dpo-full
This model is a fine-tuned version of allenai/tulu-2-7b on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
- Loss: 0.6636
- Rewards/chosen: 0.0407
- Rewards/rejected: -0.0326
- Rewards/accuracies: 0.6746
- Rewards/margins: 0.0733
- Logps/rejected: -317.3561
- Logps/chosen: -335.2600
- Logits/rejected: -1.2511
- Logits/chosen: -1.1780
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: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- 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 | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6762 | 0.4184 | 100 | 0.6753 | 0.0546 | 0.0122 | 0.6627 | 0.0424 | -312.8761 | -333.8717 | -1.2638 | -1.1861 |
| 0.6604 | 0.8368 | 200 | 0.6640 | 0.0423 | -0.0311 | 0.6706 | 0.0734 | -317.2082 | -335.1042 | -1.2523 | -1.1794 |
Framework versions
- Transformers 4.44.1
- Pytorch 2.1.2+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1