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_Adamax_1e4_20Epoch_Beit-large-224_fold1
+  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: 0.8595336076817558
+---
+
+<!-- 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_Adamax_1e4_20Epoch_Beit-large-224_fold1
+
+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: 1.4832
+- Accuracy: 0.8595
+
+## 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: 0.0001
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.3205        | 1.0   | 914  | 0.4126          | 0.8335   |
+| 0.3896        | 2.0   | 1828 | 0.3489          | 0.8595   |
+| 0.2815        | 3.0   | 2742 | 0.4941          | 0.8250   |
+| 0.0932        | 4.0   | 3656 | 0.8851          | 0.8431   |
+| 0.0061        | 5.0   | 4570 | 1.0518          | 0.8527   |
+| 0.0199        | 6.0   | 5484 | 1.2561          | 0.8529   |
+| 0.0725        | 7.0   | 6398 | 1.4266          | 0.8565   |
+| 0.0           | 8.0   | 7312 | 1.4824          | 0.8543   |
+| 0.0           | 9.0   | 8226 | 1.4678          | 0.8579   |
+| 0.0           | 10.0  | 9140 | 1.4832          | 0.8595   |
+
+
+### Framework versions
+
+- Transformers 4.32.1
+- Pytorch 2.0.1
+- Datasets 2.12.0
+- Tokenizers 0.13.2

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