--- license: apache-2.0 base_model: bert-base-uncased tags: - generated_from_trainer - Multiple Choice metrics: - accuracy model-index: - name: bert-base-uncased-e_CARE results: [] datasets: - 12ml/e-CARE language: - en pipeline_tag: question-answering --- # bert-base-uncased-e_CARE This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased). It achieves the following results on the evaluation set: - Loss: 1.7677 - Accuracy: 0.7212 ## 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: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.5637 | 1.0 | 1571 | 0.5282 | 0.7244 | | 0.345 | 2.0 | 3142 | 0.6667 | 0.7320 | | 0.1098 | 3.0 | 4713 | 1.3113 | 0.7257 | | 0.0212 | 4.0 | 6284 | 1.8194 | 0.7225 | | 0.0185 | 5.0 | 7855 | 1.7677 | 0.7212 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.2 - Tokenizers 0.13.3