Model save

README.md

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+---
+license: apache-2.0
+base_model: microsoft/swin-tiny-patch4-window7-224
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: leaftype-swin-tiny-patch4-window7-224-finetuned
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: validation
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9090909090909091
+---
+
+<!-- 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. -->
+
+# leaftype-swin-tiny-patch4-window7-224-finetuned
+
+This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2021
+- Accuracy: 0.9091
+
+## 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: 5e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 30
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.7327        | 0.94  | 12   | 0.6155          | 0.6044   |
+| 0.5479        | 1.96  | 25   | 0.4489          | 0.7936   |
+| 0.3205        | 2.98  | 38   | 0.2164          | 0.9115   |
+| 0.2386        | 4.0   | 51   | 0.2124          | 0.9115   |
+| 0.1937        | 4.94  | 63   | 0.2349          | 0.9091   |
+| 0.1884        | 5.96  | 76   | 0.1752          | 0.9214   |
+| 0.2186        | 6.98  | 89   | 0.3518          | 0.8698   |
+| 0.1833        | 8.0   | 102  | 0.2443          | 0.9017   |
+| 0.1856        | 8.94  | 114  | 0.2492          | 0.9017   |
+| 0.1605        | 9.96  | 127  | 0.2005          | 0.9189   |
+| 0.1934        | 10.98 | 140  | 0.1713          | 0.9263   |
+| 0.186         | 12.0  | 153  | 0.1573          | 0.9238   |
+| 0.1407        | 12.94 | 165  | 0.1658          | 0.9214   |
+| 0.1655        | 13.96 | 178  | 0.1570          | 0.9214   |
+| 0.1448        | 14.98 | 191  | 0.1622          | 0.9238   |
+| 0.1525        | 16.0  | 204  | 0.2110          | 0.9165   |
+| 0.1226        | 16.94 | 216  | 0.2109          | 0.9165   |
+| 0.1556        | 17.96 | 229  | 0.1914          | 0.9165   |
+| 0.1264        | 18.98 | 242  | 0.2251          | 0.9115   |
+| 0.1249        | 20.0  | 255  | 0.2863          | 0.8993   |
+| 0.1099        | 20.94 | 267  | 0.2447          | 0.9066   |
+| 0.1223        | 21.96 | 280  | 0.2358          | 0.9042   |
+| 0.1084        | 22.98 | 293  | 0.1713          | 0.9238   |
+| 0.1054        | 24.0  | 306  | 0.2085          | 0.9115   |
+| 0.1055        | 24.94 | 318  | 0.2002          | 0.9115   |
+| 0.1167        | 25.96 | 331  | 0.2289          | 0.9140   |
+| 0.1156        | 26.98 | 344  | 0.1889          | 0.9115   |
+| 0.0919        | 28.0  | 357  | 0.2015          | 0.9115   |
+| 0.0827        | 28.24 | 360  | 0.2021          | 0.9091   |
+
+
+### Framework versions
+
+- Transformers 4.38.1
+- Pytorch 1.10.0+cu111
+- Datasets 2.17.1
+- Tokenizers 0.15.2

model.safetensors

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