--- library_name: transformers license: apache-2.0 base_model: google-bert/bert-large-uncased tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: bert-large-uncased-finetuned-medmcqa-2024-11-25-T15-46-18 results: [] --- # bert-large-uncased-finetuned-medmcqa-2024-11-25-T15-46-18 This model is a fine-tuned version of [google-bert/bert-large-uncased](https://huggingface.co/google-bert/bert-large-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.3951 - Accuracy: 0.4524 - F1: 0.4646 ## 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: 4 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 8 - total_train_batch_size: 32 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 1 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:------:|:----:|:---------------:|:--------:|:------:| | 1.3793 | 0.9978 | 57 | 1.3951 | 0.4524 | 0.4646 | ### Framework versions - Transformers 4.46.2 - Pytorch 2.5.1+cu121 - Datasets 3.1.0 - Tokenizers 0.20.3