--- library_name: transformers license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_trainer metrics: - accuracy model-index: - name: distilbert-base-uncased-distilled-clinc results: [] --- # distilbert-base-uncased-distilled-clinc This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.3006 - Accuracy: 0.9406 ## 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: 48 - eval_batch_size: 48 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 7 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 318 | 1.6434 | 0.7435 | | 1.9562 | 2.0 | 636 | 0.9006 | 0.8661 | | 1.9562 | 3.0 | 954 | 0.5509 | 0.9129 | | 0.8242 | 4.0 | 1272 | 0.4011 | 0.9313 | | 0.4197 | 5.0 | 1590 | 0.3346 | 0.9390 | | 0.4197 | 6.0 | 1908 | 0.3087 | 0.9384 | | 0.2973 | 7.0 | 2226 | 0.3006 | 0.9406 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.1+cu121 - Datasets 3.0.1 - Tokenizers 0.19.1