End of training

README.md

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+---
+license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
+tags:
+- generated_from_trainer
+datasets:
+- chest-xray-classification
+metrics:
+- accuracy
+model-index:
+- name: vit-pneumonia-classification
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: chest-xray-classification
+      type: chest-xray-classification
+      config: full
+      split: validation
+      args: full
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9560951680156978
+---
+
+<!-- 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-pneumonia-classification
+
+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 chest-xray-classification dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1301
+- Accuracy: 0.9561
+
+## 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: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.4786        | 1.0   | 32   | 0.3081          | 0.8609   |
+| 0.213         | 2.0   | 64   | 0.1645          | 0.9399   |
+| 0.1724        | 3.0   | 96   | 0.1419          | 0.9502   |
+| 0.1438        | 4.0   | 128  | 0.0950          | 0.9734   |
+| 0.1267        | 5.0   | 160  | 0.1225          | 0.9579   |
+
+
+### Framework versions
+
+- Transformers 4.34.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.14.0

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