Vit 384 Tongue Image Segmented Augmented

--- library_name: transformers license: apache-2.0 base_model: google/vit-base-patch16-384 tags: - generated_from_trainer metrics: - precision - recall - f1 model-index: - name: segmented-augmented results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # segmented-augmented This model is a fine-tuned version of [google/vit-base-patch16-384](https://huggingface.co/google/vit-base-patch16-384) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.5815 - Precision: 0.8308 - Recall: 0.9136 - F1: 0.8703 ## 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 | Precision | Recall | F1 | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:| | 0.081 | 1.0 | 327 | 0.3693 | 0.8464 | 0.8970 | 0.8710 | | 0.0151 | 2.0 | 654 | 0.4906 | 0.8171 | 0.8904 | 0.8521 | | 0.0066 | 3.0 | 981 | 0.5194 | 0.8416 | 0.9003 | 0.8700 | | 0.0029 | 4.0 | 1308 | 0.5671 | 0.8308 | 0.9136 | 0.8703 | | 0.0026 | 5.0 | 1635 | 0.5815 | 0.8308 | 0.9136 | 0.8703 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.1+cu121 - Datasets 3.0.0 - Tokenizers 0.19.1

Source context: 80 downloads · 0 likes · Pipeline image-classification · Library transformers · Repo e1010101/vit-384-tongue-image-segmented-augmented

Source context: 2 downloads · 0 likes · Pipeline image-classification · Library transformers · Repo e1010101/vit-384-tongue-image-segmented-augmented