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: hushem_40x_beit_large_adamax_00001_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: 0.8444444444444444
+---
+
+<!-- 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_large_adamax_00001_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: 1.5239
+- Accuracy: 0.8444
+
+## 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: 1e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- 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: 50
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 0.0134        | 1.0   | 215   | 0.7143          | 0.7556   |
+| 0.0005        | 2.0   | 430   | 0.8825          | 0.8444   |
+| 0.0002        | 3.0   | 645   | 1.1645          | 0.8      |
+| 0.0002        | 4.0   | 860   | 1.1853          | 0.8      |
+| 0.0001        | 5.0   | 1075  | 1.2007          | 0.8      |
+| 0.0001        | 6.0   | 1290  | 1.1677          | 0.8222   |
+| 0.0006        | 7.0   | 1505  | 1.1023          | 0.8222   |
+| 0.0001        | 8.0   | 1720  | 1.5156          | 0.7333   |
+| 0.0           | 9.0   | 1935  | 1.1716          | 0.8222   |
+| 0.0           | 10.0  | 2150  | 1.2763          | 0.8222   |
+| 0.0           | 11.0  | 2365  | 1.1176          | 0.8444   |
+| 0.0           | 12.0  | 2580  | 1.2233          | 0.8444   |
+| 0.0023        | 13.0  | 2795  | 1.5312          | 0.8      |
+| 0.0           | 14.0  | 3010  | 1.3548          | 0.8      |
+| 0.0           | 15.0  | 3225  | 1.2898          | 0.8222   |
+| 0.0           | 16.0  | 3440  | 1.2810          | 0.8222   |
+| 0.0           | 17.0  | 3655  | 1.3480          | 0.8222   |
+| 0.0           | 18.0  | 3870  | 1.2231          | 0.8444   |
+| 0.0           | 19.0  | 4085  | 1.2120          | 0.8444   |
+| 0.0           | 20.0  | 4300  | 1.3990          | 0.8222   |
+| 0.0           | 21.0  | 4515  | 1.3925          | 0.8222   |
+| 0.0           | 22.0  | 4730  | 1.3055          | 0.8444   |
+| 0.0           | 23.0  | 4945  | 1.3624          | 0.8222   |
+| 0.0           | 24.0  | 5160  | 1.3420          | 0.8222   |
+| 0.0           | 25.0  | 5375  | 1.3903          | 0.8222   |
+| 0.0           | 26.0  | 5590  | 1.3025          | 0.8444   |
+| 0.0           | 27.0  | 5805  | 1.3676          | 0.8444   |
+| 0.0           | 28.0  | 6020  | 1.3843          | 0.8444   |
+| 0.0           | 29.0  | 6235  | 1.4718          | 0.8      |
+| 0.0           | 30.0  | 6450  | 1.4946          | 0.8222   |
+| 0.0           | 31.0  | 6665  | 1.5006          | 0.8222   |
+| 0.0           | 32.0  | 6880  | 1.5270          | 0.8222   |
+| 0.0           | 33.0  | 7095  | 1.6386          | 0.8      |
+| 0.0           | 34.0  | 7310  | 1.5335          | 0.8222   |
+| 0.0           | 35.0  | 7525  | 1.5020          | 0.8444   |
+| 0.0           | 36.0  | 7740  | 1.5220          | 0.8444   |
+| 0.0           | 37.0  | 7955  | 1.6305          | 0.8      |
+| 0.0           | 38.0  | 8170  | 1.5482          | 0.8      |
+| 0.0           | 39.0  | 8385  | 1.5491          | 0.8      |
+| 0.0           | 40.0  | 8600  | 1.5716          | 0.8222   |
+| 0.0           | 41.0  | 8815  | 1.5929          | 0.8222   |
+| 0.0           | 42.0  | 9030  | 1.5745          | 0.8222   |
+| 0.0           | 43.0  | 9245  | 1.4702          | 0.8444   |
+| 0.0           | 44.0  | 9460  | 1.4777          | 0.8444   |
+| 0.0           | 45.0  | 9675  | 1.4961          | 0.8444   |
+| 0.0           | 46.0  | 9890  | 1.5108          | 0.8444   |
+| 0.0           | 47.0  | 10105 | 1.5228          | 0.8444   |
+| 0.0           | 48.0  | 10320 | 1.5215          | 0.8444   |
+| 0.0           | 49.0  | 10535 | 1.5246          | 0.8444   |
+| 0.0032        | 50.0  | 10750 | 1.5239          | 0.8444   |
+
+
+### Framework versions
+
+- Transformers 4.32.1
+- Pytorch 2.1.0+cu121
+- Datasets 2.12.0
+- Tokenizers 0.13.2

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