End of training

README.md

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+---
+license: apache-2.0
+base_model: microsoft/beit-large-patch16-224
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: Boya2_3Class_RMSprop_1e5_20Epoch_Beit-large-224_fold5
+  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: 0.8631752125034274
+---
+
+<!-- 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. -->
+
+# Boya2_3Class_RMSprop_1e5_20Epoch_Beit-large-224_fold5
+
+This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.6377
+- Accuracy: 0.8632
+
+## 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: 1e-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
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.4668        | 1.0   | 914  | 0.3852          | 0.8385   |
+| 0.2261        | 2.0   | 1828 | 0.3623          | 0.8645   |
+| 0.1143        | 3.0   | 2742 | 0.5165          | 0.8580   |
+| 0.2149        | 4.0   | 3656 | 0.7493          | 0.8626   |
+| 0.1035        | 5.0   | 4570 | 1.0893          | 0.8607   |
+| 0.0224        | 6.0   | 5484 | 1.3211          | 0.8582   |
+| 0.0055        | 7.0   | 6398 | 1.5211          | 0.8604   |
+| 0.0001        | 8.0   | 7312 | 1.6383          | 0.8563   |
+| 0.0001        | 9.0   | 8226 | 1.6304          | 0.8678   |
+| 0.0           | 10.0  | 9140 | 1.6377          | 0.8632   |
+
+
+### Framework versions
+
+- Transformers 4.32.1
+- Pytorch 2.0.1
+- Datasets 2.12.0
+- Tokenizers 0.13.2

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