End of training

README.md

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+---
+license: apache-2.0
+base_model: facebook/deit-tiny-patch16-224
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: smids_3x_deit_tiny_sgd_0001_fold3
+  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: 0.7683333333333333
+---
+
+<!-- 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. -->
+
+# smids_3x_deit_tiny_sgd_0001_fold3
+
+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: 0.6313
+- Accuracy: 0.7683
+
+## 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: 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 1.2114        | 1.0   | 225   | 1.2115          | 0.3783   |
+| 1.0735        | 2.0   | 450   | 1.1384          | 0.3983   |
+| 1.097         | 3.0   | 675   | 1.1002          | 0.4133   |
+| 1.0469        | 4.0   | 900   | 1.0702          | 0.4533   |
+| 1.0229        | 5.0   | 1125  | 1.0448          | 0.48     |
+| 0.99          | 6.0   | 1350  | 1.0213          | 0.5      |
+| 0.9781        | 7.0   | 1575  | 0.9993          | 0.5117   |
+| 0.9907        | 8.0   | 1800  | 0.9784          | 0.54     |
+| 0.927         | 9.0   | 2025  | 0.9582          | 0.545    |
+| 0.8847        | 10.0  | 2250  | 0.9391          | 0.5583   |
+| 0.9329        | 11.0  | 2475  | 0.9207          | 0.5733   |
+| 0.8984        | 12.0  | 2700  | 0.9031          | 0.59     |
+| 0.8494        | 13.0  | 2925  | 0.8859          | 0.605    |
+| 0.8194        | 14.0  | 3150  | 0.8694          | 0.6183   |
+| 0.7869        | 15.0  | 3375  | 0.8536          | 0.6283   |
+| 0.8309        | 16.0  | 3600  | 0.8389          | 0.635    |
+| 0.7966        | 17.0  | 3825  | 0.8246          | 0.64     |
+| 0.8108        | 18.0  | 4050  | 0.8113          | 0.64     |
+| 0.801         | 19.0  | 4275  | 0.7985          | 0.6533   |
+| 0.771         | 20.0  | 4500  | 0.7864          | 0.66     |
+| 0.7097        | 21.0  | 4725  | 0.7747          | 0.67     |
+| 0.7109        | 22.0  | 4950  | 0.7636          | 0.6767   |
+| 0.7079        | 23.0  | 5175  | 0.7529          | 0.6867   |
+| 0.7294        | 24.0  | 5400  | 0.7431          | 0.69     |
+| 0.7458        | 25.0  | 5625  | 0.7335          | 0.6883   |
+| 0.6793        | 26.0  | 5850  | 0.7246          | 0.6917   |
+| 0.6665        | 27.0  | 6075  | 0.7159          | 0.7017   |
+| 0.6522        | 28.0  | 6300  | 0.7080          | 0.7083   |
+| 0.7013        | 29.0  | 6525  | 0.7004          | 0.715    |
+| 0.6636        | 30.0  | 6750  | 0.6932          | 0.7183   |
+| 0.6224        | 31.0  | 6975  | 0.6867          | 0.72     |
+| 0.6822        | 32.0  | 7200  | 0.6803          | 0.725    |
+| 0.6885        | 33.0  | 7425  | 0.6745          | 0.7283   |
+| 0.6623        | 34.0  | 7650  | 0.6692          | 0.7333   |
+| 0.6059        | 35.0  | 7875  | 0.6642          | 0.735    |
+| 0.6546        | 36.0  | 8100  | 0.6598          | 0.7417   |
+| 0.6233        | 37.0  | 8325  | 0.6556          | 0.7433   |
+| 0.6474        | 38.0  | 8550  | 0.6519          | 0.7467   |
+| 0.606         | 39.0  | 8775  | 0.6483          | 0.75     |
+| 0.6243        | 40.0  | 9000  | 0.6453          | 0.755    |
+| 0.6167        | 41.0  | 9225  | 0.6425          | 0.7567   |
+| 0.6518        | 42.0  | 9450  | 0.6401          | 0.7617   |
+| 0.5844        | 43.0  | 9675  | 0.6380          | 0.7633   |
+| 0.6425        | 44.0  | 9900  | 0.6361          | 0.7633   |
+| 0.6354        | 45.0  | 10125 | 0.6346          | 0.7633   |
+| 0.5465        | 46.0  | 10350 | 0.6333          | 0.765    |
+| 0.6036        | 47.0  | 10575 | 0.6324          | 0.7667   |
+| 0.5553        | 48.0  | 10800 | 0.6318          | 0.7683   |
+| 0.6342        | 49.0  | 11025 | 0.6314          | 0.7683   |
+| 0.5635        | 50.0  | 11250 | 0.6313          | 0.7683   |
+
+
+### Framework versions
+
+- Transformers 4.32.1
+- Pytorch 2.1.1+cu121
+- Datasets 2.12.0
+- Tokenizers 0.13.2

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