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_f1
+  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: 0.8888888888888888
+---
+
+<!-- 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_f1
+
+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: 0.9231
+- Accuracy: 0.8889
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.0764        | 1.0   | 107  | 0.7220          | 0.8      |
+| 0.0168        | 2.0   | 214  | 1.0516          | 0.8      |
+| 0.0193        | 2.99  | 321  | 1.1697          | 0.7556   |
+| 0.0111        | 4.0   | 429  | 0.9218          | 0.8222   |
+| 0.0033        | 5.0   | 536  | 1.0001          | 0.8444   |
+| 0.0048        | 6.0   | 643  | 1.0798          | 0.8222   |
+| 0.0           | 6.99  | 750  | 0.9561          | 0.8667   |
+| 0.0           | 8.0   | 858  | 0.9979          | 0.8444   |
+| 0.0           | 9.0   | 965  | 0.9770          | 0.8667   |
+| 0.0           | 9.98  | 1070 | 0.9231          | 0.8889   |
+
+
+### Framework versions
+
+- Transformers 4.35.0
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1