End of training

README.md

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+---
+license: apache-2.0
+base_model: google/vit-base-patch16-224
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: vit-base-patch16-224-finetuned-pneumonia-detection
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: test
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9728260869565217
+---
+
+<!-- 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-finetuned-pneumonia-detection
+
+This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0938
+- Accuracy: 0.9728
+
+## 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: 64
+- eval_batch_size: 64
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 256
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.2082        | 0.99  | 20   | 0.1462          | 0.9402   |
+| 0.0832        | 1.98  | 40   | 0.0998          | 0.9658   |
+| 0.0517        | 2.96  | 60   | 0.0938          | 0.9728   |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.1.2
+- Datasets 2.18.0
+- Tokenizers 0.15.2

all_results.json

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+{
+    "epoch": 2.96,
+    "eval_accuracy": 0.9728260869565217,
+    "eval_loss": 0.09380105137825012,
+    "eval_runtime": 33.986,
+    "eval_samples_per_second": 37.898,
+    "eval_steps_per_second": 0.618
+}

eval_results.json

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+{
+    "epoch": 2.96,
+    "eval_accuracy": 0.9728260869565217,
+    "eval_loss": 0.09380105137825012,
+    "eval_runtime": 33.986,
+    "eval_samples_per_second": 37.898,
+    "eval_steps_per_second": 0.618
+}