Model save

README.md

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+---
+license: apache-2.0
+base_model: microsoft/swinv2-tiny-patch4-window8-256
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: swinv2-tiny-patch4-window8-256-finalterm
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.878125
+---
+
+<!-- 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. -->
+
+# swinv2-tiny-patch4-window8-256-finalterm
+
+This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3239
+- Accuracy: 0.8781
+
+## 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: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.397         | 1.0   | 10   | 1.3486          | 0.3563   |
+| 1.2224        | 2.0   | 20   | 1.0746          | 0.5094   |
+| 0.8883        | 3.0   | 30   | 0.7386          | 0.7094   |
+| 0.73          | 4.0   | 40   | 0.6787          | 0.7188   |
+| 0.6132        | 5.0   | 50   | 0.5557          | 0.75     |
+| 0.5297        | 6.0   | 60   | 0.4564          | 0.8281   |
+| 0.4811        | 7.0   | 70   | 0.4000          | 0.8594   |
+| 0.484         | 8.0   | 80   | 0.4082          | 0.8531   |
+| 0.4525        | 9.0   | 90   | 0.3568          | 0.8906   |
+| 0.429         | 10.0  | 100  | 0.3661          | 0.875    |
+| 0.4383        | 11.0  | 110  | 0.4052          | 0.85     |
+| 0.4586        | 12.0  | 120  | 0.3318          | 0.8812   |
+| 0.4036        | 13.0  | 130  | 0.3540          | 0.8656   |
+| 0.3652        | 14.0  | 140  | 0.3942          | 0.8719   |
+| 0.3822        | 15.0  | 150  | 0.3421          | 0.8906   |
+| 0.3564        | 16.0  | 160  | 0.3174          | 0.8969   |
+| 0.3635        | 17.0  | 170  | 0.3357          | 0.8844   |
+| 0.3645        | 18.0  | 180  | 0.3204          | 0.8938   |
+| 0.3576        | 19.0  | 190  | 0.3307          | 0.8781   |
+| 0.3532        | 20.0  | 200  | 0.3239          | 0.8781   |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.2
+- Tokenizers 0.19.1

model.safetensors

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