--- license: apache-2.0 library_name: peft tags: - trl - sft - unsloth - generated_from_trainer base_model: unsloth/llama-3-8b-Instruct-bnb-4bit model-index: - name: llama3-2M-MedEV results: [] --- # llama3-2M-MedEV This model is a fine-tuned version of [unsloth/llama-3-8b-Instruct-bnb-4bit](https://huggingface.co/unsloth/llama-3-8b-Instruct-bnb-4bit) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.4249 - Bleu: 47.7973 ## 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: 0.0002 - train_batch_size: 32 - eval_batch_size: 16 - seed: 3407 - gradient_accumulation_steps: 4 - total_train_batch_size: 128 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 1.534 | 0.1200 | 320 | 1.4902 | | 1.3171 | 0.2399 | 640 | 1.4705 | | 1.29 | 0.3599 | 960 | 1.4644 | | 1.2699 | 0.4798 | 1280 | 1.4287 | | 1.2567 | 0.5998 | 1600 | 1.4576 | | 1.2448 | 0.7197 | 1920 | 1.4196 | | 1.2353 | 0.8397 | 2240 | 1.4249 | | 1.2274 | 0.9596 | 2560 | 1.4172 | | 1.1635 | 1.0796 | 2880 | 1.4180 | | 1.1337 | 1.1995 | 3200 | 1.4219 | | 1.1346 | 1.3195 | 3520 | 1.3954 | | 1.131 | 1.4394 | 3840 | 1.3714 | | 1.1325 | 1.5594 | 4160 | 1.3923 | | 1.1269 | 1.6793 | 4480 | 1.4118 | | 1.1221 | 1.7993 | 4800 | 1.4251 | | 1.1226 | 1.9192 | 5120 | 1.3970 | | 1.0898 | 2.0392 | 5440 | 1.4198 | | 1.0372 | 2.1591 | 5760 | 1.4310 | | 1.0325 | 2.2791 | 6080 | 1.4209 | | 1.0334 | 2.3990 | 6400 | 1.4205 | | 1.0328 | 2.5190 | 6720 | 1.4306 | | 1.0303 | 2.6389 | 7040 | 1.4222 | | 1.0283 | 2.7589 | 7360 | 1.4266 | | 1.0273 | 2.8788 | 7680 | 1.4251 | | 1.0295 | 2.9988 | 8000 | 1.4249 | ### Framework versions - PEFT 0.10.0 - Transformers 4.40.2 - Pytorch 2.3.0 - Datasets 2.19.1 - Tokenizers 0.19.1