--- license: mit tags: - generated_from_trainer metrics: - accuracy model-index: - name: claim-classifier results: [] --- # claim-classifier This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.3432 - Accuracy: 0.8889 ## 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: 5e-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: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.048 | 1.0 | 562 | 0.3966 | 0.8669 | | 0.3896 | 2.0 | 1124 | 0.4440 | 0.8669 | | 0.4783 | 3.0 | 1686 | 0.3893 | 0.8699 | | 0.4792 | 4.0 | 2248 | 0.4019 | 0.8689 | | 1.2405 | 5.0 | 2810 | 0.3883 | 0.8729 | | 0.0996 | 6.0 | 3372 | 0.3673 | 0.8669 | | 0.4833 | 7.0 | 3934 | 0.3873 | 0.8759 | | 0.2461 | 8.0 | 4496 | 0.3646 | 0.8659 | | 0.0977 | 9.0 | 5058 | 0.3432 | 0.8889 | | 0.0682 | 10.0 | 5620 | 0.3458 | 0.8919 | ### Framework versions - Transformers 4.30.2 - Pytorch 1.8.1 - Datasets 2.13.2 - Tokenizers 0.13.3