--- license: apache-2.0 tags: - generated_from_trainer datasets: - clinc_oos metrics: - accuracy model-index: - name: distilbert-base-uncased-distilled-clinc results: - task: name: Text Classification type: text-classification dataset: name: clinc_oos type: clinc_oos args: plus metrics: - name: Accuracy type: accuracy value: 0.9467741935483871 --- # distilbert-base-uncased-distilled-clinc This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the clinc_oos dataset. It achieves the following results on the evaluation set: - Loss: 0.2525 - Accuracy: 0.9468 ## 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: 10 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 4.2246 | 1.0 | 318 | 3.1584 | 0.7545 | | 2.4033 | 2.0 | 636 | 1.5656 | 0.8652 | | 1.1684 | 3.0 | 954 | 0.7795 | 0.9161 | | 0.5693 | 4.0 | 1272 | 0.4653 | 0.9329 | | 0.3042 | 5.0 | 1590 | 0.3412 | 0.9406 | | 0.1794 | 6.0 | 1908 | 0.2912 | 0.9403 | | 0.1184 | 7.0 | 2226 | 0.2654 | 0.9461 | | 0.0873 | 8.0 | 2544 | 0.2557 | 0.9439 | | 0.0719 | 9.0 | 2862 | 0.2549 | 0.9465 | | 0.0646 | 10.0 | 3180 | 0.2525 | 0.9468 | ### Framework versions - Transformers 4.18.0 - Pytorch 1.11.0 - Datasets 2.0.0 - Tokenizers 0.12.1