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_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: 0.8452742359846185
+---
+
+<!-- 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_fold3
+
+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: 1.6691
+- Accuracy: 0.8453
+
+## 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 0.4597        | 1.0   | 2467  | 0.3981          | 0.8379   |
+| 0.3536        | 2.0   | 4934  | 0.3996          | 0.8368   |
+| 0.1795        | 3.0   | 7401  | 0.4872          | 0.8467   |
+| 0.1625        | 4.0   | 9868  | 0.6122          | 0.8475   |
+| 0.1107        | 5.0   | 12335 | 0.9789          | 0.8460   |
+| 0.0003        | 6.0   | 14802 | 1.0818          | 0.8494   |
+| 0.0149        | 7.0   | 17269 | 1.4834          | 0.8465   |
+| 0.0           | 8.0   | 19736 | 1.5090          | 0.8474   |
+| 0.0           | 9.0   | 22203 | 1.5763          | 0.8462   |
+| 0.001         | 10.0  | 24670 | 1.6691          | 0.8453   |
+
+
+### Framework versions
+
+- Transformers 4.32.1
+- Pytorch 2.0.1
+- Datasets 2.12.0
+- Tokenizers 0.13.2

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