--- library_name: transformers license: llama3.1 base_model: meta-llama/Meta-Llama-3.1-8B tags: - llama-factory - full - generated_from_trainer model-index: - name: oh-dcft-v3.1-llama-3.1-nemotron-70b results: [] --- # oh-dcft-v3.1-llama-3.1-nemotron-70b This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B) on the mlfoundations-dev/oh-dcft-v3.1-llama-3.1-nemotron-70b dataset. It achieves the following results on the evaluation set: - Loss: 0.5541 ## 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: 8 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - num_devices: 8 - gradient_accumulation_steps: 8 - total_train_batch_size: 512 - total_eval_batch_size: 64 - 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: constant - num_epochs: 3.0 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.5897 | 0.9998 | 539 | 0.5783 | | 0.519 | 1.9995 | 1078 | 0.5572 | | 0.469 | 2.9993 | 1617 | 0.5541 | ### Framework versions - Transformers 4.46.1 - Pytorch 2.3.0 - Datasets 3.1.0 - Tokenizers 0.20.3