Model save

README.md

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+---
+license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
+tags:
+- generated_from_trainer
+datasets:
+- image_folder
+metrics:
+- accuracy
+model-index:
+- name: vit-base-patch16-224-in21k-finetuned-cxr
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: image_folder
+      type: image_folder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9266281945589447
+---
+
+<!-- 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. -->
+
+# vit-base-patch16-224-in21k-finetuned-cxr
+
+This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the image_folder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1879
+- Accuracy: 0.9266
+
+## 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: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 15
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.2994        | 0.99  | 85   | 0.3337          | 0.8854   |
+| 0.2806        | 2.0   | 171  | 0.2670          | 0.9101   |
+| 0.2519        | 2.99  | 256  | 0.2495          | 0.9134   |
+| 0.2456        | 4.0   | 342  | 0.2450          | 0.9143   |
+| 0.2094        | 4.99  | 427  | 0.2105          | 0.9258   |
+| 0.1808        | 6.0   | 513  | 0.1984          | 0.9308   |
+| 0.1959        | 6.99  | 598  | 0.2022          | 0.9258   |
+| 0.179         | 8.0   | 684  | 0.1980          | 0.9299   |
+| 0.1915        | 8.99  | 769  | 0.1889          | 0.9308   |
+| 0.1735        | 10.0  | 855  | 0.1931          | 0.9324   |
+| 0.174         | 10.99 | 940  | 0.1872          | 0.9324   |
+| 0.167         | 12.0  | 1026 | 0.1758          | 0.9357   |
+| 0.1408        | 12.99 | 1111 | 0.1890          | 0.9349   |
+| 0.1442        | 14.0  | 1197 | 0.1849          | 0.9324   |
+| 0.1661        | 14.91 | 1275 | 0.1879          | 0.9266   |
+
+
+### Framework versions
+
+- Transformers 4.36.0
+- Pytorch 2.0.0
+- Datasets 2.1.0
+- Tokenizers 0.15.0

model.safetensors

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