--- license: apache-2.0 tags: - generated_from_trainer datasets: - eoir_privacy metrics: - accuracy - f1 model-index: - name: distilbert-base-uncased-finetuned-eoir_privacy results: - task: name: Text Classification type: text-classification dataset: name: eoir_privacy type: eoir_privacy args: all metrics: - name: Accuracy type: accuracy value: 0.9052835051546392 - name: F1 type: f1 value: 0.8088426527958388 --- # distilbert-base-uncased-finetuned-eoir_privacy This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the eoir_privacy dataset. It achieves the following results on the evaluation set: - Loss: 0.3681 - Accuracy: 0.9053 - F1: 0.8088 ## 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: 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 | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | No log | 1.0 | 395 | 0.3053 | 0.8789 | 0.7432 | | 0.3562 | 2.0 | 790 | 0.2857 | 0.8976 | 0.7883 | | 0.2217 | 3.0 | 1185 | 0.3358 | 0.8905 | 0.7550 | | 0.1509 | 4.0 | 1580 | 0.3505 | 0.9040 | 0.8077 | | 0.1509 | 5.0 | 1975 | 0.3681 | 0.9053 | 0.8088 | ### Framework versions - Transformers 4.18.0 - Pytorch 1.11.0+cu113 - Datasets 2.1.0 - Tokenizers 0.12.1