--- license: apache-2.0 base_model: microsoft/beit-large-patch16-384 tags: - image-classification - vision - generated_from_trainer metrics: - accuracy model-index: - name: beit-large-patch16-384-limb-person-crop-8_5e-5_1e-3_0.15 results: [] --- # beit-large-patch16-384-limb-person-crop-8_5e-5_1e-3_0.15 This model is a fine-tuned version of [microsoft/beit-large-patch16-384](https://huggingface.co/microsoft/beit-large-patch16-384) on the c14kevincardenas/beta_caller_284_person_crop dataset. It achieves the following results on the evaluation set: - Loss: 1.3535 - Accuracy: 0.3483 ## 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: 32 - eval_batch_size: 32 - seed: 2014 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - num_epochs: 10.0 - mixed_precision_training: Native AMP - label_smoothing_factor: 0.15 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 1.3404 | 1.0 | 214 | 1.4186 | 0.3980 | | 1.3839 | 2.0 | 428 | 1.3841 | 0.2703 | | 1.3931 | 3.0 | 642 | 1.3867 | 0.2745 | | 1.3889 | 4.0 | 856 | 1.3884 | 0.2745 | | 1.3864 | 5.0 | 1070 | 1.3842 | 0.2761 | | 1.3892 | 6.0 | 1284 | 1.3802 | 0.2877 | | 1.369 | 7.0 | 1498 | 1.3726 | 0.3143 | | 1.3545 | 8.0 | 1712 | 1.3627 | 0.3275 | | 1.3626 | 9.0 | 1926 | 1.3594 | 0.3391 | | 1.3464 | 10.0 | 2140 | 1.3535 | 0.3483 | ### Framework versions - Transformers 4.41.0.dev0 - Pytorch 2.0.1+cu117 - Datasets 2.19.1 - Tokenizers 0.19.1