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_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: 0.8489055533036076
+---
+
+<!-- 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_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: 1.5710
+- Accuracy: 0.8489
+
+## 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 0.3726        | 1.0   | 2468  | 0.3949          | 0.8399   |
+| 0.325         | 2.0   | 4936  | 0.4383          | 0.8328   |
+| 0.2727        | 3.0   | 7404  | 0.4165          | 0.8467   |
+| 0.067         | 4.0   | 9872  | 0.6221          | 0.8448   |
+| 0.0057        | 5.0   | 12340 | 1.0252          | 0.8438   |
+| 0.0004        | 6.0   | 14808 | 1.0541          | 0.8462   |
+| 0.0155        | 7.0   | 17276 | 1.3852          | 0.8511   |
+| 0.0047        | 8.0   | 19744 | 1.4084          | 0.8509   |
+| 0.0007        | 9.0   | 22212 | 1.5540          | 0.8503   |
+| 0.0           | 10.0  | 24680 | 1.5710          | 0.8489   |
+
+
+### Framework versions
+
+- Transformers 4.32.1
+- Pytorch 2.0.1
+- Datasets 2.12.0
+- Tokenizers 0.13.2

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