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: Boya1_SGD_1-e3_20Epoch_Deit-tiny-patch16_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: 0.3950583763236492
+---
+
+<!-- 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. -->
+
+# Boya1_SGD_1-e3_20Epoch_Deit-tiny-patch16_fold1
+
+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: 1.8160
+- Accuracy: 0.3951
+
+## 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: 16
+- eval_batch_size: 16
+- 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 2.4438        | 1.0   | 924   | 2.4927          | 0.1898   |
+| 2.3969        | 2.0   | 1848  | 2.3384          | 0.2389   |
+| 2.2609        | 3.0   | 2772  | 2.2168          | 0.2878   |
+| 2.0421        | 4.0   | 3696  | 2.1285          | 0.3068   |
+| 2.0227        | 5.0   | 4620  | 2.0634          | 0.3296   |
+| 1.99          | 6.0   | 5544  | 2.0084          | 0.3397   |
+| 1.9954        | 7.0   | 6468  | 1.9664          | 0.3549   |
+| 2.0727        | 8.0   | 7392  | 1.9354          | 0.3652   |
+| 2.0158        | 9.0   | 8316  | 1.9072          | 0.3704   |
+| 1.8488        | 10.0  | 9240  | 1.8880          | 0.3750   |
+| 1.8985        | 11.0  | 10164 | 1.8721          | 0.3790   |
+| 1.7309        | 12.0  | 11088 | 1.8576          | 0.3812   |
+| 1.8129        | 13.0  | 12012 | 1.8465          | 0.3899   |
+| 1.7599        | 14.0  | 12936 | 1.8384          | 0.3866   |
+| 1.7902        | 15.0  | 13860 | 1.8309          | 0.3894   |
+| 1.7502        | 16.0  | 14784 | 1.8250          | 0.3932   |
+| 1.7034        | 17.0  | 15708 | 1.8221          | 0.3934   |
+| 1.8587        | 18.0  | 16632 | 1.8187          | 0.3940   |
+| 1.8137        | 19.0  | 17556 | 1.8165          | 0.3942   |
+| 1.9039        | 20.0  | 18480 | 1.8160          | 0.3951   |
+
+
+### Framework versions
+
+- Transformers 4.40.1
+- Pytorch 2.1.0
+- Datasets 2.19.0
+- Tokenizers 0.19.1