--- library_name: transformers license: apache-2.0 base_model: mistralai/Mistral-7B-v0.3 tags: - llama-factory - full - generated_from_trainer model-index: - name: mistral_7b_0-3_oh-dcft-v3.1-llama-3.1-nemotron-70b results: [] --- # mistral_7b_0-3_oh-dcft-v3.1-llama-3.1-nemotron-70b This model is a fine-tuned version of [mistralai/Mistral-7B-v0.3](https://huggingface.co/mistralai/Mistral-7B-v0.3) on the mlfoundations-dev/oh-dcft-v3.1-llama-3.1-nemotron-70b dataset. It achieves the following results on the evaluation set: - Loss: 0.4800 ## 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: 16 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - num_devices: 32 - total_train_batch_size: 512 - total_eval_batch_size: 256 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine_with_min_lr - lr_scheduler_warmup_ratio: 0.05 - num_epochs: 3.0 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 0.4706 | 1.0 | 640 | 0.4657 | | 0.369 | 2.0 | 1280 | 0.4541 | | 0.287 | 3.0 | 1920 | 0.4800 | ### Framework versions - Transformers 4.46.1 - Pytorch 2.4.0 - Datasets 3.0.2 - Tokenizers 0.20.3