--- license: apache-2.0 tags: - generated_from_trainer datasets: - yelp_review_full metrics: - accuracy model-index: - name: Bert_Classifier results: - task: name: Text Classification type: text-classification dataset: name: yelp_review_full type: yelp_review_full config: yelp_review_full split: train args: yelp_review_full metrics: - name: Accuracy type: accuracy value: 0.634 --- # Bert_Classifier This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the yelp_review_full dataset. It achieves the following results on the evaluation set: - Loss: 1.0546 - Accuracy: 0.634 ## 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: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.9528 | 1.0 | 2500 | 0.9097 | 0.5985 | | 0.7607 | 2.0 | 5000 | 0.8969 | 0.627 | | 0.5039 | 3.0 | 7500 | 1.0546 | 0.634 | ### Framework versions - Transformers 4.21.3 - Pytorch 1.12.1+cu113 - Datasets 2.4.0 - Tokenizers 0.12.1