--- 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: dcft_orca-agentinstruct-1M-v1-cleaned-singleturn results: [] --- # dcft_orca-agentinstruct-1M-v1-cleaned-singleturn 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/dcft_orca-agentinstruct-1M-v1-cleaned-singleturn dataset. It achieves the following results on the evaluation set: - Loss: 0.4835 ## 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: 32 - gradient_accumulation_steps: 2 - 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: constant - lr_scheduler_warmup_ratio: 0.1 - lr_scheduler_warmup_steps: 1738 - num_epochs: 3.0 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.4886 | 0.9993 | 674 | 0.4894 | | 0.4288 | 2.0 | 1349 | 0.4789 | | 0.382 | 2.9978 | 2022 | 0.4835 | ### Framework versions - Transformers 4.46.1 - Pytorch 2.3.0 - Datasets 3.0.2 - Tokenizers 0.20.3