--- base_model: bert-base-uncased library_name: transformers license: apache-2.0 metrics: - accuracy - f1 - precision - recall tags: - generated_from_trainer model-index: - name: results results: [] --- # results This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.2886 - Accuracy: 0.6 - F1: 0.5849 - Precision: 0.6185 - Recall: 0.6 ## 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: 2e-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 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| | No log | 1.0 | 79 | 1.2014 | 0.552 | 0.4206 | 0.7106 | 0.552 | | 1.1506 | 2.0 | 158 | 1.0758 | 0.572 | 0.5046 | 0.6200 | 0.572 | | 0.8847 | 3.0 | 237 | 1.0723 | 0.59 | 0.5568 | 0.5521 | 0.59 | | 0.7512 | 4.0 | 316 | 1.0845 | 0.578 | 0.5676 | 0.6152 | 0.578 | | 0.7512 | 5.0 | 395 | 1.1433 | 0.574 | 0.5576 | 0.5480 | 0.574 | | 0.6091 | 6.0 | 474 | 1.2274 | 0.57 | 0.5683 | 0.5766 | 0.57 | | 0.496 | 7.0 | 553 | 1.2917 | 0.562 | 0.5493 | 0.5634 | 0.562 | | 0.4066 | 8.0 | 632 | 1.2886 | 0.6 | 0.5849 | 0.6185 | 0.6 | | 0.3591 | 9.0 | 711 | 1.3574 | 0.56 | 0.5592 | 0.5768 | 0.56 | | 0.3591 | 10.0 | 790 | 1.3527 | 0.566 | 0.5590 | 0.5706 | 0.566 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.5.0+cu121 - Datasets 3.1.0 - Tokenizers 0.19.1