End of training

README.md

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+---
+license: apache-2.0
+base_model: microsoft/beit-base-patch16-224-pt22k-ft22k
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: hushem_40x_beit_base_f3
+  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: 0.8837209302325582
+---
+
+<!-- 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. -->
+
+# hushem_40x_beit_base_f3
+
+This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9422
+- Accuracy: 0.8837
+
+## 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: 5e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 64
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.0594        | 1.0   | 108  | 0.4441          | 0.8372   |
+| 0.0595        | 2.0   | 217  | 0.8725          | 0.8605   |
+| 0.0173        | 3.0   | 325  | 0.5866          | 0.9070   |
+| 0.0084        | 4.0   | 434  | 0.6360          | 0.8605   |
+| 0.0005        | 5.0   | 542  | 0.6191          | 0.8837   |
+| 0.0008        | 6.0   | 651  | 0.6635          | 0.9070   |
+| 0.0008        | 7.0   | 759  | 0.8772          | 0.8837   |
+| 0.0001        | 8.0   | 868  | 0.8012          | 0.9070   |
+| 0.0           | 9.0   | 976  | 0.9139          | 0.8837   |
+| 0.0001        | 9.95  | 1080 | 0.9422          | 0.8837   |
+
+
+### Framework versions
+
+- Transformers 4.35.0
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1

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