End of training

README.md

@@ -0,0 +1,95 @@
+---
+license: apache-2.0
+base_model: facebook/deit-tiny-patch16-224
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: hushem_conflu_deneme_fold5
+  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: 0.6341463414634146
+---
+
+<!-- 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_conflu_deneme_fold5
+
+This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.9630
+- Accuracy: 0.6341
+
+## 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: 0.001
+- 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: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 6    | 1.4708          | 0.2439   |
+| 1.7951        | 2.0   | 12   | 1.3099          | 0.2439   |
+| 1.7951        | 3.0   | 18   | 1.1130          | 0.4146   |
+| 1.2772        | 4.0   | 24   | 1.0471          | 0.7073   |
+| 1.1124        | 5.0   | 30   | 1.2680          | 0.5366   |
+| 1.1124        | 6.0   | 36   | 1.0908          | 0.5122   |
+| 0.9481        | 7.0   | 42   | 1.5674          | 0.3902   |
+| 0.9481        | 8.0   | 48   | 0.8947          | 0.6098   |
+| 0.9653        | 9.0   | 54   | 1.1885          | 0.6098   |
+| 0.639         | 10.0  | 60   | 0.9898          | 0.6585   |
+| 0.639         | 11.0  | 66   | 1.7943          | 0.4634   |
+| 0.5108        | 12.0  | 72   | 1.7088          | 0.5366   |
+| 0.5108        | 13.0  | 78   | 1.6432          | 0.5610   |
+| 0.1679        | 14.0  | 84   | 1.5598          | 0.5854   |
+| 0.1286        | 15.0  | 90   | 2.1600          | 0.5854   |
+| 0.1286        | 16.0  | 96   | 1.9849          | 0.5854   |
+| 0.0501        | 17.0  | 102  | 1.9630          | 0.6341   |
+| 0.0501        | 18.0  | 108  | 1.9630          | 0.6341   |
+| 0.0271        | 19.0  | 114  | 1.9630          | 0.6341   |
+| 0.0437        | 20.0  | 120  | 1.9630          | 0.6341   |
+
+
+### Framework versions
+
+- Transformers 4.35.0
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1

model.safetensors

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