--- library_name: transformers license: llama3.1 base_model: meta-llama/Llama-3.1-8B tags: - llama-factory - full - generated_from_trainer model-index: - name: OH_DCFT_V3_wo_evol_instruct_70k results: [] --- # OH_DCFT_V3_wo_evol_instruct_70k 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/OH_DCFT_V3_wo_evol_instruct_70k dataset. It achieves the following results on the evaluation set: - Loss: 0.6311 ## 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: 16 - gradient_accumulation_steps: 4 - total_train_batch_size: 512 - total_eval_batch_size: 128 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - 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 | |:-------------:|:------:|:----:|:---------------:| | 0.6447 | 0.9994 | 391 | 0.6408 | | 0.5993 | 1.9987 | 782 | 0.6304 | | 0.5618 | 2.9981 | 1173 | 0.6311 | ### Framework versions - Transformers 4.45.2 - Pytorch 2.3.0 - Datasets 2.21.0 - Tokenizers 0.20.1