--- license: apache-2.0 base_model: bert-base-uncased tags: - generated_from_trainer metrics: - accuracy model-index: - name: bert_multiple_choice results: [] --- # bert_multiple_choice This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.4499 - Accuracy: 0.535 ## 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: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:-----:|:---------------:|:--------:| | 1.4892 | 1.0 | 3207 | 1.2930 | 0.485 | | 1.2722 | 2.0 | 6414 | 1.2277 | 0.47 | | 1.1139 | 3.0 | 9621 | 1.1827 | 0.495 | | 0.9607 | 4.0 | 12828 | 1.1426 | 0.55 | | 0.8117 | 5.0 | 16035 | 1.1891 | 0.53 | | 0.6878 | 6.0 | 19242 | 1.1941 | 0.53 | | 0.5874 | 7.0 | 22449 | 1.2868 | 0.54 | | 0.4989 | 8.0 | 25656 | 1.3710 | 0.55 | | 0.4274 | 9.0 | 28863 | 1.4499 | 0.535 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu117 - Datasets 2.14.4 - Tokenizers 0.13.3