--- license: apache-2.0 base_model: bert-base-uncased tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: BERT_without_preprocessing_grid_search results: [] --- # BERT_without_preprocessing_grid_search 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: 0.6705 - Precision: 0.8452 - Recall: 0.8581 - F1: 0.8510 - Accuracy: 0.8818 ## 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: 3e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | No log | 1.0 | 257 | 0.5962 | 0.7414 | 0.8132 | 0.7626 | 0.8268 | | 0.7597 | 2.0 | 514 | 0.5120 | 0.8170 | 0.8507 | 0.8292 | 0.8652 | | 0.7597 | 3.0 | 771 | 0.4818 | 0.7975 | 0.8565 | 0.8202 | 0.8652 | | 0.2391 | 4.0 | 1028 | 0.5223 | 0.8220 | 0.8613 | 0.8377 | 0.8652 | | 0.2391 | 5.0 | 1285 | 0.5516 | 0.8172 | 0.8599 | 0.8347 | 0.8706 | | 0.1316 | 6.0 | 1542 | 0.5747 | 0.8139 | 0.8593 | 0.8333 | 0.8710 | | 0.1316 | 7.0 | 1799 | 0.6290 | 0.8332 | 0.8483 | 0.8386 | 0.8701 | | 0.0773 | 8.0 | 2056 | 0.6089 | 0.8312 | 0.8620 | 0.8450 | 0.8764 | | 0.0773 | 9.0 | 2313 | 0.6633 | 0.8384 | 0.8532 | 0.8448 | 0.8774 | | 0.0633 | 10.0 | 2570 | 0.6705 | 0.8452 | 0.8581 | 0.8510 | 0.8818 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.4 - Tokenizers 0.13.3