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_fold4
+  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: 0.8628524500410621
+---
+
+<!-- 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_fold4
+
+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: 1.5247
+- Accuracy: 0.8629
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.3762        | 1.0   | 913  | 0.3808          | 0.8420   |
+| 0.3285        | 2.0   | 1826 | 0.3567          | 0.8566   |
+| 0.216         | 3.0   | 2739 | 0.4224          | 0.8494   |
+| 0.2451        | 4.0   | 3652 | 0.6798          | 0.8598   |
+| 0.0553        | 5.0   | 4565 | 1.0822          | 0.8483   |
+| 0.0017        | 6.0   | 5478 | 1.2537          | 0.8503   |
+| 0.0008        | 7.0   | 6391 | 1.3944          | 0.8552   |
+| 0.0002        | 8.0   | 7304 | 1.4327          | 0.8585   |
+| 0.0001        | 9.0   | 8217 | 1.5474          | 0.8661   |
+| 0.0           | 10.0  | 9130 | 1.5247          | 0.8629   |
+
+
+### Framework versions
+
+- Transformers 4.32.1
+- Pytorch 2.0.1
+- Datasets 2.12.0
+- Tokenizers 0.13.2

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