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: Karma_3Class_3Class_Adamax_1e4_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: 0.8534020827014458
+---
+
+<!-- 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. -->
+
+# Karma_3Class_3Class_Adamax_1e4_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: 1.5433
+- Accuracy: 0.8534
+
+## 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 0.3595        | 1.0   | 2466  | 0.4309          | 0.8251   |
+| 0.3101        | 2.0   | 4932  | 0.3865          | 0.8447   |
+| 0.1826        | 3.0   | 7398  | 0.4588          | 0.8485   |
+| 0.1658        | 4.0   | 9864  | 0.5997          | 0.8504   |
+| 0.1373        | 5.0   | 12330 | 0.8549          | 0.8498   |
+| 0.0639        | 6.0   | 14796 | 1.1026          | 0.8527   |
+| 0.0234        | 7.0   | 17262 | 1.2762          | 0.8538   |
+| 0.0001        | 8.0   | 19728 | 1.4347          | 0.8547   |
+| 0.0           | 9.0   | 22194 | 1.5139          | 0.8518   |
+| 0.0002        | 10.0  | 24660 | 1.5433          | 0.8534   |
+
+
+### Framework versions
+
+- Transformers 4.32.1
+- Pytorch 2.0.1
+- Datasets 2.12.0
+- Tokenizers 0.13.2

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