--- license: apache-2.0 base_model: jordyvl/vit-base_rvl-cdip tags: - generated_from_trainer metrics: - accuracy model-index: - name: vit-base_rvl_cdip-N1K_AURC_256 results: [] --- # vit-base_rvl_cdip-N1K_AURC_256 This model is a fine-tuned version of [jordyvl/vit-base_rvl-cdip](https://huggingface.co/jordyvl/vit-base_rvl-cdip) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.2459 - Accuracy: 0.8968 - Brier Loss: 0.1720 - Nll: 0.9246 - F1 Micro: 0.8968 - F1 Macro: 0.8967 - Ece: 0.0709 - Aurc: 0.0191 ## 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: 256 - eval_batch_size: 256 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | Brier Loss | Nll | F1 Micro | F1 Macro | Ece | Aurc | |:-------------:|:-----:|:----:|:---------------:|:--------:|:----------:|:------:|:--------:|:--------:|:------:|:------:| | No log | 1.0 | 63 | 0.1138 | 0.8922 | 0.1604 | 1.1695 | 0.8922 | 0.8926 | 0.0478 | 0.0170 | | No log | 2.0 | 126 | 0.1565 | 0.8952 | 0.1607 | 1.1000 | 0.8952 | 0.8952 | 0.0532 | 0.0176 | | No log | 3.0 | 189 | 0.1722 | 0.8972 | 0.1620 | 1.0250 | 0.8972 | 0.8973 | 0.0584 | 0.0175 | | No log | 4.0 | 252 | 0.2006 | 0.897 | 0.1642 | 0.9921 | 0.897 | 0.8969 | 0.0615 | 0.0181 | | No log | 5.0 | 315 | 0.2142 | 0.8988 | 0.1668 | 0.9670 | 0.8988 | 0.8986 | 0.0640 | 0.0183 | | No log | 6.0 | 378 | 0.2207 | 0.8975 | 0.1688 | 0.9482 | 0.8975 | 0.8975 | 0.0674 | 0.0186 | | No log | 7.0 | 441 | 0.2310 | 0.897 | 0.1700 | 0.9397 | 0.897 | 0.8969 | 0.0697 | 0.0188 | | 0.008 | 8.0 | 504 | 0.2401 | 0.8968 | 0.1714 | 0.9268 | 0.8968 | 0.8966 | 0.0705 | 0.0190 | | 0.008 | 9.0 | 567 | 0.2441 | 0.8975 | 0.1719 | 0.9262 | 0.8975 | 0.8974 | 0.0709 | 0.0191 | | 0.008 | 10.0 | 630 | 0.2459 | 0.8968 | 0.1720 | 0.9246 | 0.8968 | 0.8967 | 0.0709 | 0.0191 | ### Framework versions - Transformers 4.33.3 - Pytorch 2.2.0.dev20231002 - Datasets 2.7.1 - Tokenizers 0.13.3