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: Boya1_SGD_1-e3_20Epoch_Deit-tiny-patch16_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: 0.42884199134199136
+---
+
+<!-- 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_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: 1.7155
+- Accuracy: 0.4288
+
+## 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 2.4106        | 1.0   | 923   | 2.4578          | 0.2002   |
+| 2.3587        | 2.0   | 1846  | 2.2972          | 0.2516   |
+| 2.1274        | 3.0   | 2769  | 2.1627          | 0.3055   |
+| 2.1583        | 4.0   | 3692  | 2.0604          | 0.3279   |
+| 1.9036        | 5.0   | 4615  | 1.9842          | 0.3458   |
+| 1.7721        | 6.0   | 5538  | 1.9243          | 0.3582   |
+| 1.9867        | 7.0   | 6461  | 1.8782          | 0.3726   |
+| 1.8532        | 8.0   | 7384  | 1.8428          | 0.3891   |
+| 1.8503        | 9.0   | 8307  | 1.8165          | 0.4004   |
+| 1.79          | 10.0  | 9230  | 1.7943          | 0.4037   |
+| 1.7717        | 11.0  | 10153 | 1.7761          | 0.4091   |
+| 1.7696        | 12.0  | 11076 | 1.7613          | 0.4148   |
+| 1.7298        | 13.0  | 11999 | 1.7507          | 0.4191   |
+| 1.7468        | 14.0  | 12922 | 1.7401          | 0.4210   |
+| 1.6085        | 15.0  | 13845 | 1.7322          | 0.4229   |
+| 1.7188        | 16.0  | 14768 | 1.7257          | 0.4278   |
+| 1.7307        | 17.0  | 15691 | 1.7212          | 0.4259   |
+| 1.5257        | 18.0  | 16614 | 1.7177          | 0.4275   |
+| 1.6729        | 19.0  | 17537 | 1.7160          | 0.4294   |
+| 1.7293        | 20.0  | 18460 | 1.7155          | 0.4288   |
+
+
+### Framework versions
+
+- Transformers 4.40.1
+- Pytorch 2.1.0
+- Datasets 2.19.0
+- Tokenizers 0.19.1

model.safetensors

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