End of training

README.md

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+---
+license: apache-2.0
+base_model: microsoft/swin-large-patch4-window7-224-in22k
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: Boya2_SGD_1e3_20Epoch_Swin-large-224_fold3
+  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: 0.4703308722996992
+---
+
+<!-- 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_SGD_1e3_20Epoch_Swin-large-224_fold3
+
+This model is a fine-tuned version of [microsoft/swin-large-patch4-window7-224-in22k](https://huggingface.co/microsoft/swin-large-patch4-window7-224-in22k) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.7253
+- Accuracy: 0.4703
+
+## 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: 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: 20
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 2.4987        | 1.0   | 913   | 2.4779          | 0.2773   |
+| 2.2499        | 2.0   | 1826  | 2.3076          | 0.2986   |
+| 2.1231        | 3.0   | 2739  | 2.2022          | 0.3325   |
+| 2.1706        | 4.0   | 3652  | 2.1236          | 0.3672   |
+| 2.0969        | 5.0   | 4565  | 2.0581          | 0.3940   |
+| 1.9524        | 6.0   | 5478  | 2.0029          | 0.4085   |
+| 1.9868        | 7.0   | 6391  | 1.9548          | 0.4208   |
+| 1.9729        | 8.0   | 7304  | 1.9129          | 0.4293   |
+| 1.9817        | 9.0   | 8217  | 1.8827          | 0.4331   |
+| 1.9117        | 10.0  | 9130  | 1.8505          | 0.4430   |
+| 1.8805        | 11.0  | 10043 | 1.8244          | 0.4482   |
+| 1.8198        | 12.0  | 10956 | 1.8053          | 0.4528   |
+| 1.7002        | 13.0  | 11869 | 1.7829          | 0.4558   |
+| 1.811         | 14.0  | 12782 | 1.7721          | 0.4602   |
+| 1.8637        | 15.0  | 13695 | 1.7553          | 0.4602   |
+| 1.8566        | 16.0  | 14608 | 1.7454          | 0.4654   |
+| 1.742         | 17.0  | 15521 | 1.7350          | 0.4665   |
+| 1.692         | 18.0  | 16434 | 1.7303          | 0.4695   |
+| 1.8241        | 19.0  | 17347 | 1.7261          | 0.4695   |
+| 1.8203        | 20.0  | 18260 | 1.7253          | 0.4703   |
+
+
+### Framework versions
+
+- Transformers 4.32.1
+- Pytorch 2.1.1+cu121
+- Datasets 2.21.0
+- Tokenizers 0.13.2