--- library_name: transformers license: apache-2.0 base_model: distilbert/distilbert-base-uncased tags: - generated_from_trainer metrics: - accuracy model-index: - name: absa-restaurants-distilbert-base-uncased results: [] --- # absa-restaurants-distilbert-base-uncased This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.5845 - Accuracy: 0.7918 ## 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: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 226 | 0.7111 | 0.7337 | | No log | 2.0 | 452 | 0.6517 | 0.7444 | | 0.6945 | 3.0 | 678 | 0.6291 | 0.7605 | | 0.6945 | 4.0 | 904 | 0.5985 | 0.7837 | | 0.4252 | 5.0 | 1130 | 0.5845 | 0.7918 | ### Framework versions - Transformers 4.48.2 - Pytorch 2.5.1+cu124 - Datasets 3.2.0 - Tokenizers 0.21.0