--- license: apache-2.0 base_model: BioMistral/BioMistral-7B tags: - alignment-handbook - trl - sft - generated_from_trainer - trl - sft - generated_from_trainer datasets: - HuggingFaceH4/deita-10k-v0-sft model-index: - name: biomistral-7b-wo-kqa_golden-iter-sft-step1_gamma0 results: [] --- # biomistral-7b-wo-kqa_golden-iter-sft-step1_gamma0 This model is a fine-tuned version of [BioMistral/BioMistral-7B](https://huggingface.co/BioMistral/BioMistral-7B) on the HuggingFaceH4/deita-10k-v0-sft dataset. It achieves the following results on the evaluation set: - Loss: 2.2919 ## 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: 2e-05 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - distributed_type: multi-GPU - num_devices: 4 - gradient_accumulation_steps: 4 - total_train_batch_size: 64 - total_eval_batch_size: 16 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 1.8934 | 0.95 | 13 | 1.9087 | | 0.9275 | 1.96 | 27 | 2.0545 | | 0.4857 | 2.84 | 39 | 2.2919 | ### Framework versions - Transformers 4.38.2 - Pytorch 2.1.2+cu121 - Datasets 2.14.6 - Tokenizers 0.15.2