--- library_name: transformers license: apache-2.0 base_model: google-bert/bert-base-uncased tags: - generated_from_trainer metrics: - accuracy model-index: - name: bert-base-uncased results: [] --- # bert-base-uncased This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.0001 - Accuracy: 1.0 ## 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: 0.0001 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.4121 | 1.0 | 7 | 0.0812 | 1.0 | | 0.0404 | 2.0 | 14 | 0.0032 | 1.0 | | 0.0024 | 3.0 | 21 | 0.0004 | 1.0 | | 0.0004 | 4.0 | 28 | 0.0002 | 1.0 | | 0.0002 | 5.0 | 35 | 0.0001 | 1.0 | | 0.0059 | 6.0 | 42 | 0.0001 | 1.0 | | 0.0001 | 7.0 | 49 | 0.0001 | 1.0 | | 0.0002 | 8.0 | 56 | 0.0001 | 1.0 | | 0.0001 | 9.0 | 63 | 0.0001 | 1.0 | | 0.0001 | 10.0 | 70 | 0.0001 | 1.0 | ### Framework versions - Transformers 4.50.3 - Pytorch 2.6.0+cu124 - Datasets 3.5.0 - Tokenizers 0.21.1