--- library_name: transformers license: apache-2.0 base_model: bert-base-uncased tags: - generated_from_trainer metrics: - accuracy model-index: - name: bert-base-uncased-finetuned-rte-run_3 results: [] --- # bert-base-uncased-finetuned-rte-run_3 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: 0.6883 - Accuracy: 0.6462 ## 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: 9.796937080527387e-06 - train_batch_size: 64 - 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 39 | 0.6887 | 0.5307 | | No log | 2.0 | 78 | 0.6797 | 0.5596 | | No log | 3.0 | 117 | 0.6805 | 0.5523 | | No log | 4.0 | 156 | 0.6554 | 0.6354 | | No log | 5.0 | 195 | 0.6759 | 0.6245 | | No log | 6.0 | 234 | 0.6883 | 0.6462 | | No log | 7.0 | 273 | 0.7252 | 0.6137 | | No log | 8.0 | 312 | 0.7378 | 0.6318 | | No log | 9.0 | 351 | 0.7529 | 0.6282 | | No log | 10.0 | 390 | 0.7541 | 0.6318 | ### Framework versions - Transformers 4.50.3 - Pytorch 2.6.0+cu124 - Datasets 3.5.0 - Tokenizers 0.21.1