--- license: apache-2.0 tags: - generated_from_trainer datasets: - clinc_oos metrics: - accuracy model-index: - name: distilbert-base-uncased-finetuned-clinc results: - task: name: Text Classification type: text-classification dataset: name: clinc_oos type: clinc_oos config: plus split: train args: plus metrics: - name: Accuracy type: accuracy value: 0.9503225806451613 --- # distilbert-base-uncased-finetuned-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: 0.2339 - Accuracy: 0.9503 ## 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: 12 - eval_batch_size: 12 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 3.2073 | 1.0 | 1271 | 1.3840 | 0.8542 | | 0.7452 | 2.0 | 2542 | 0.4053 | 0.9316 | | 0.1916 | 3.0 | 3813 | 0.2580 | 0.9452 | | 0.0768 | 4.0 | 5084 | 0.2371 | 0.9477 | | 0.0455 | 5.0 | 6355 | 0.2339 | 0.9503 | ### Framework versions - Transformers 4.21.3 - Pytorch 1.12.1 - Datasets 2.4.0 - Tokenizers 0.12.1