dpo-llama3-8b-sample-rules
This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1915
- Rewards/chosen: 0.1004
- Rewards/rejected: -1.6031
- Rewards/accuracies: 1.0
- Rewards/margins: 1.7035
- Logps/rejected: -517.5475
- Logps/chosen: -200.9981
- Logits/rejected: -1.3936
- Logits/chosen: -1.2455
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: 1
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- 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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.4345 | 0.4444 | 50 | 0.3859 | 0.2018 | -0.5860 | 1.0 | 0.7877 | -415.8305 | -190.8644 | -1.3991 | -1.2723 |
| 0.2288 | 0.8889 | 100 | 0.1915 | 0.1004 | -1.6031 | 1.0 | 1.7035 | -517.5475 | -200.9981 | -1.3936 | -1.2455 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for hannahbillo/dpo-llama3-8b-sample-rules
Base model
meta-llama/Llama-3.1-8B