--- license: apache-2.0 base_model: mistralai/Mistral-7B-v0.1 tags: - generated_from_trainer model-index: - name: results results: [] --- # results This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.6218 ## 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-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - num_epochs: 2 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:-----:|:---------------:| | 0.9667 | 0.07 | 500 | 0.8561 | | 0.8253 | 0.14 | 1000 | 0.7976 | | 0.7771 | 0.2 | 1500 | 0.7676 | | 0.7623 | 0.27 | 2000 | 0.7459 | | 0.7399 | 0.34 | 2500 | 0.7269 | | 0.7253 | 0.41 | 3000 | 0.7166 | | 0.7241 | 0.47 | 3500 | 0.7035 | | 0.7063 | 0.54 | 4000 | 0.6962 | | 0.6857 | 0.61 | 4500 | 0.6883 | | 0.6909 | 0.68 | 5000 | 0.6829 | | 0.6754 | 0.75 | 5500 | 0.6731 | | 0.6803 | 0.81 | 6000 | 0.6657 | | 0.6659 | 0.88 | 6500 | 0.6599 | | 0.6603 | 0.95 | 7000 | 0.6556 | | 0.6249 | 1.02 | 7500 | 0.6610 | | 0.53 | 1.09 | 8000 | 0.6583 | | 0.5246 | 1.15 | 8500 | 0.6544 | | 0.5204 | 1.22 | 9000 | 0.6515 | | 0.5135 | 1.29 | 9500 | 0.6498 | | 0.5165 | 1.36 | 10000 | 0.6433 | | 0.518 | 1.42 | 10500 | 0.6410 | | 0.5032 | 1.49 | 11000 | 0.6368 | | 0.5091 | 1.56 | 11500 | 0.6335 | | 0.5038 | 1.63 | 12000 | 0.6307 | | 0.4907 | 1.7 | 12500 | 0.6302 | | 0.5006 | 1.76 | 13000 | 0.6262 | | 0.4823 | 1.83 | 13500 | 0.6239 | | 0.4906 | 1.9 | 14000 | 0.6225 | | 0.4905 | 1.97 | 14500 | 0.6218 | ### Framework versions - Transformers 4.36.0.dev0 - Pytorch 2.1.0+cu118 - Datasets 2.15.0 - Tokenizers 0.15.0