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:
+- beans
+metrics:
+- accuracy
+model-index:
+- name: beans_image_classification
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: beans
+      type: beans
+      config: default
+      split: train[:500]
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.96
+---
+
+<!-- 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. -->
+
+# beans_image_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 beans dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1072
+- Accuracy: 0.96
+
+## 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: 0.001
+- train_batch_size: 12
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 48
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 0.94  | 8    | 1.3666          | 0.66     |
+| 0.3651        | 2.0   | 17   | 0.3823          | 0.84     |
+| 0.5622        | 2.94  | 25   | 0.3333          | 0.86     |
+| 0.3373        | 4.0   | 34   | 0.1274          | 0.97     |
+| 0.2055        | 4.94  | 42   | 0.1882          | 0.93     |
+| 0.1819        | 6.0   | 51   | 0.2265          | 0.9      |
+| 0.1819        | 6.94  | 59   | 0.2395          | 0.91     |
+| 0.2428        | 8.0   | 68   | 0.1451          | 0.97     |
+| 0.1305        | 8.94  | 76   | 0.1554          | 0.94     |
+| 0.1203        | 9.41  | 80   | 0.1705          | 0.92     |
+
+
+### Framework versions
+
+- Transformers 4.34.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.14.1

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