--- library_name: transformers license: apache-2.0 base_model: Qwen/Qwen2.5-7B tags: - llama-factory - full - generated_from_trainer model-index: - name: hp_ablations_qwen_bsz1024_dcftv1.2 results: [] --- # hp_ablations_qwen_bsz1024_dcftv1.2 This model is a fine-tuned version of [Qwen/Qwen2.5-7B](https://huggingface.co/Qwen/Qwen2.5-7B) on the mlfoundations-dev/oh-dcft-v1.2_no-curation_gpt-4o-mini dataset. It achieves the following results on the evaluation set: - Loss: 0.6337 ## 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: 8 - total_train_batch_size: 1024 - total_eval_batch_size: 128 - 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 | |:-------------:|:------:|:----:|:---------------:| | 0.6429 | 0.9949 | 170 | 0.6456 | | 0.6126 | 1.9927 | 340 | 0.6363 | | 0.5898 | 2.9905 | 510 | 0.6337 | ### Framework versions - Transformers 4.46.1 - Pytorch 2.3.0 - Datasets 3.0.2 - Tokenizers 0.20.3