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: Boya1_3Class_RMSprop_1e5_20Epoch_Beit-large-224_fold2
+  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: 0.8445945945945946
+---
+
+<!-- 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. -->
+
+# Boya1_3Class_RMSprop_1e5_20Epoch_Beit-large-224_fold2
+
+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: 0.4945
+- Accuracy: 0.8446
+
+## 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: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.4285        | 1.0   | 923  | 0.4438          | 0.8349   |
+| 0.3029        | 2.0   | 1846 | 0.4037          | 0.8522   |
+| 0.1901        | 3.0   | 2769 | 0.4945          | 0.8446   |
+
+
+### Framework versions
+
+- Transformers 4.32.1
+- Pytorch 2.0.1
+- Datasets 2.12.0
+- Tokenizers 0.13.2

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