--- license: apache-2.0 base_model: distilbert-base-uncased 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 config: plus split: validation args: plus metrics: - name: Accuracy type: accuracy value: 0.9409677419354838 --- # 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: 0.1001 - Accuracy: 0.9410 ## 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 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 318 | 0.5771 | 0.7258 | | 0.7611 | 2.0 | 636 | 0.2843 | 0.8845 | | 0.7611 | 3.0 | 954 | 0.1780 | 0.9261 | | 0.2794 | 4.0 | 1272 | 0.1381 | 0.9310 | | 0.1598 | 5.0 | 1590 | 0.1207 | 0.9335 | | 0.1598 | 6.0 | 1908 | 0.1119 | 0.9384 | | 0.1244 | 7.0 | 2226 | 0.1064 | 0.9410 | | 0.1104 | 8.0 | 2544 | 0.1027 | 0.9413 | | 0.1104 | 9.0 | 2862 | 0.1006 | 0.9416 | | 0.1038 | 10.0 | 3180 | 0.1001 | 0.9410 | ### Framework versions - Transformers 4.32.1 - Pytorch 2.0.1+cu118 - Datasets 2.14.4 - Tokenizers 0.13.3