--- library_name: transformers license: apache-2.0 base_model: google-bert/bert-base-uncased tags: - generated_from_trainer metrics: - accuracy model-index: - name: my_model results: [] --- # my_model This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.3020 - Accuracy: 0.9151 ## 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: 16 - eval_batch_size: 16 - 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: 2 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 433 | 0.2575 | 0.9117 | | 0.3114 | 2.0 | 866 | 0.3020 | 0.9151 | ### Framework versions - Transformers 4.49.0 - Pytorch 2.6.0+cpu - Datasets 3.3.1 - Tokenizers 0.21.0