olivia-7b-dpo-lora-v2
This model is a fine-tuned version of Open-Orca/Mistral-7B-OpenOrca on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2452
- Rewards/chosen: -0.7312
- Rewards/rejected: -2.7785
- Rewards/accuracies: 0.9132
- Rewards/margins: 2.0473
- Logps/rejected: -92.7458
- Logps/chosen: -70.4321
- Logits/rejected: -2.6590
- Logits/chosen: -2.6728
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: 3e-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 32
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.2434 | 1.0 | 109 | 0.2452 | -0.7312 | -2.7785 | 0.9132 | 2.0473 | -92.7458 | -70.4321 | -2.6590 | -2.6728 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.1+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
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Model tree for prd-nguyenvo/olivia-7b-dpo-lora-v2
Base model
Open-Orca/Mistral-7B-OpenOrca