--- 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_aAURC_2 results: [] --- # vit-base_rvl_cdip-N1K_aAURC_2 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: 0.3354 - Accuracy: 0.8788 - Brier Loss: 0.2243 - Nll: 1.0945 - F1 Micro: 0.8788 - F1 Macro: 0.8793 - Ece: 0.1094 - Aurc: 0.0303 ## 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: 2 - eval_batch_size: 2 - 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 | |:-------------:|:-----:|:-----:|:---------------:|:--------:|:----------:|:------:|:--------:|:--------:|:------:|:------:| | 0.1996 | 1.0 | 8000 | 0.2395 | 0.8413 | 0.2593 | 1.3668 | 0.8413 | 0.8446 | 0.1016 | 0.0414 | | 0.1357 | 2.0 | 16000 | 0.2446 | 0.8545 | 0.2435 | 1.2587 | 0.8545 | 0.8550 | 0.1066 | 0.0364 | | 0.1083 | 3.0 | 24000 | 0.2702 | 0.8515 | 0.2584 | 1.2968 | 0.8515 | 0.8528 | 0.1126 | 0.0379 | | 0.0578 | 4.0 | 32000 | 0.3397 | 0.8327 | 0.2931 | 1.3827 | 0.8327 | 0.8322 | 0.1391 | 0.0494 | | 0.0294 | 5.0 | 40000 | 0.3407 | 0.8538 | 0.2662 | 1.3685 | 0.8537 | 0.8536 | 0.1280 | 0.0378 | | 0.0099 | 6.0 | 48000 | 0.3489 | 0.8585 | 0.2602 | 1.2438 | 0.8585 | 0.8599 | 0.1254 | 0.0350 | | 0.0058 | 7.0 | 56000 | 0.3433 | 0.868 | 0.2418 | 1.2328 | 0.868 | 0.8666 | 0.1172 | 0.0362 | | 0.0026 | 8.0 | 64000 | 0.3414 | 0.87 | 0.2401 | 1.1910 | 0.87 | 0.8704 | 0.1162 | 0.0304 | | 0.0026 | 9.0 | 72000 | 0.3460 | 0.8728 | 0.2357 | 1.1567 | 0.8728 | 0.8729 | 0.1143 | 0.0308 | | 0.0024 | 10.0 | 80000 | 0.3354 | 0.8788 | 0.2243 | 1.0945 | 0.8788 | 0.8793 | 0.1094 | 0.0303 | ### Framework versions - Transformers 4.33.3 - Pytorch 2.2.0.dev20231002 - Datasets 2.7.1 - Tokenizers 0.13.3