--- library_name: transformers license: llama3 base_model: meta-llama/Meta-Llama-3-8B-Instruct tags: - trl - dpo - generated_from_trainer model-index: - name: Llama0-3-8b-v0.1-p-0.05-lr5e-7-e1 results: [] --- # Llama0-3-8b-v0.1-p-0.05-lr5e-7-e1 This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.6417 - Rewards/chosen: -0.5291 - Rewards/rejected: -0.5936 - Rewards/accuracies: 0.5968 - Rewards/margins: 0.0645 - Logps/rejected: -146.1117 - Logps/chosen: -141.1991 - Logits/rejected: 0.1599 - Logits/chosen: 0.1449 ## 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: 2 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - num_devices: 8 - gradient_accumulation_steps: 8 - 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: linear - num_epochs: 1.0 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| | 0.6655 | 0.2137 | 100 | 0.6653 | -0.0372 | -0.0437 | 0.5847 | 0.0065 | -91.1306 | -92.0131 | 0.0596 | 0.0396 | | 0.6569 | 0.4275 | 200 | 0.6557 | -0.1710 | -0.1939 | 0.6089 | 0.0230 | -106.1501 | -105.3901 | 0.1033 | 0.0850 | | 0.646 | 0.6412 | 300 | 0.6467 | -0.3795 | -0.4276 | 0.6008 | 0.0480 | -129.5149 | -126.2473 | 0.1520 | 0.1356 | | 0.6441 | 0.8549 | 400 | 0.6425 | -0.4991 | -0.5612 | 0.5887 | 0.0622 | -142.8797 | -138.2009 | 0.1546 | 0.1390 | ### Framework versions - Transformers 4.45.1 - Pytorch 2.4.1+cu121 - Datasets 3.0.0 - Tokenizers 0.20.0