--- library_name: transformers license: llama3.1 base_model: meta-llama/Llama-3.1-8B tags: - llama-factory - full - generated_from_trainer model-index: - name: llama3_mammoth_dcft_ablation_original_50k results: [] --- # llama3_mammoth_dcft_ablation_original_50k This model is a fine-tuned version of [meta-llama/Llama-3.1-8B](https://huggingface.co/meta-llama/Llama-3.1-8B) on the mlfoundations-dev/wia_dcft_webinstruct_original_uniform_50k dataset. It achieves the following results on the evaluation set: - Loss: 0.0594 ## 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: 4 - seed: 42 - distributed_type: multi-GPU - num_devices: 4 - gradient_accumulation_steps: 16 - total_train_batch_size: 512 - total_eval_batch_size: 16 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: constant - lr_scheduler_warmup_ratio: 0.1 - lr_scheduler_warmup_steps: 1738 - num_epochs: 3.0 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | No log | 0.896 | 7 | 0.0652 | | 1.0796 | 1.96 | 15 | 0.0610 | | 0.9233 | 2.768 | 21 | 0.0594 | ### Framework versions - Transformers 4.46.1 - Pytorch 2.5.1+cu121 - Datasets 3.1.0 - Tokenizers 0.20.3