End of training

README.md

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+---
+license: apache-2.0
+base_model: facebook/deit-small-patch16-224
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: smids_3x_deit_small_rms_00001_fold1
+  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: 0.9081803005008348
+---
+
+<!-- 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_small_rms_00001_fold1
+
+This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8163
+- Accuracy: 0.9082
+
+## 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 0.3764        | 1.0   | 226   | 0.2918          | 0.8831   |
+| 0.2061        | 2.0   | 452   | 0.2699          | 0.8998   |
+| 0.0904        | 3.0   | 678   | 0.3139          | 0.8915   |
+| 0.1028        | 4.0   | 904   | 0.4241          | 0.8948   |
+| 0.0553        | 5.0   | 1130  | 0.4370          | 0.9032   |
+| 0.0029        | 6.0   | 1356  | 0.6281          | 0.8965   |
+| 0.0117        | 7.0   | 1582  | 0.5524          | 0.9065   |
+| 0.0491        | 8.0   | 1808  | 0.6970          | 0.8915   |
+| 0.0376        | 9.0   | 2034  | 0.6152          | 0.9065   |
+| 0.0001        | 10.0  | 2260  | 0.7198          | 0.9015   |
+| 0.003         | 11.0  | 2486  | 0.7173          | 0.8898   |
+| 0.0001        | 12.0  | 2712  | 0.6506          | 0.9048   |
+| 0.0002        | 13.0  | 2938  | 0.8916          | 0.8831   |
+| 0.0132        | 14.0  | 3164  | 0.7369          | 0.8982   |
+| 0.0192        | 15.0  | 3390  | 0.7968          | 0.8982   |
+| 0.0001        | 16.0  | 3616  | 0.7098          | 0.9082   |
+| 0.026         | 17.0  | 3842  | 0.7751          | 0.8965   |
+| 0.0001        | 18.0  | 4068  | 0.7904          | 0.9015   |
+| 0.0054        | 19.0  | 4294  | 0.6956          | 0.9032   |
+| 0.0           | 20.0  | 4520  | 0.7178          | 0.9032   |
+| 0.0008        | 21.0  | 4746  | 0.7487          | 0.9098   |
+| 0.0089        | 22.0  | 4972  | 0.7031          | 0.9115   |
+| 0.0027        | 23.0  | 5198  | 0.7177          | 0.9032   |
+| 0.0           | 24.0  | 5424  | 0.7262          | 0.9082   |
+| 0.0           | 25.0  | 5650  | 0.7421          | 0.9082   |
+| 0.0001        | 26.0  | 5876  | 0.7360          | 0.9082   |
+| 0.0           | 27.0  | 6102  | 0.7465          | 0.9065   |
+| 0.0           | 28.0  | 6328  | 0.8372          | 0.9048   |
+| 0.0           | 29.0  | 6554  | 0.8930          | 0.8898   |
+| 0.0           | 30.0  | 6780  | 0.7924          | 0.9098   |
+| 0.0339        | 31.0  | 7006  | 0.8291          | 0.8998   |
+| 0.0           | 32.0  | 7232  | 0.7573          | 0.9032   |
+| 0.0031        | 33.0  | 7458  | 0.7513          | 0.9082   |
+| 0.0           | 34.0  | 7684  | 0.8005          | 0.8998   |
+| 0.0           | 35.0  | 7910  | 0.7724          | 0.9065   |
+| 0.0           | 36.0  | 8136  | 0.7954          | 0.9065   |
+| 0.0           | 37.0  | 8362  | 0.7930          | 0.9082   |
+| 0.0           | 38.0  | 8588  | 0.8339          | 0.9048   |
+| 0.0           | 39.0  | 8814  | 0.7697          | 0.9115   |
+| 0.0           | 40.0  | 9040  | 0.7910          | 0.9082   |
+| 0.003         | 41.0  | 9266  | 0.7950          | 0.9048   |
+| 0.0027        | 42.0  | 9492  | 0.8033          | 0.9048   |
+| 0.0           | 43.0  | 9718  | 0.7969          | 0.9065   |
+| 0.0           | 44.0  | 9944  | 0.8077          | 0.9065   |
+| 0.0           | 45.0  | 10170 | 0.8102          | 0.9098   |
+| 0.0           | 46.0  | 10396 | 0.8111          | 0.9082   |
+| 0.0           | 47.0  | 10622 | 0.8142          | 0.9082   |
+| 0.0           | 48.0  | 10848 | 0.8155          | 0.9082   |
+| 0.0           | 49.0  | 11074 | 0.8163          | 0.9082   |
+| 0.0           | 50.0  | 11300 | 0.8163          | 0.9082   |
+
+
+### Framework versions
+
+- Transformers 4.32.1
+- Pytorch 2.1.0+cu121
+- Datasets 2.12.0
+- Tokenizers 0.13.2

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