Model save

README.md

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+---
+license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: vit-clothes-classification
+  results: []
+---
+
+<!-- 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. -->
+
+# vit-clothes-classification
+
+This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.7642
+- Accuracy: 0.6989
+
+## 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: 0.0002
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 8
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| 1.0975        | 0.5714 | 500  | 1.2619          | 0.6111   |
+| 0.8315        | 1.1429 | 1000 | 1.3133          | 0.6322   |
+| 0.7266        | 1.7143 | 1500 | 1.2077          | 0.6356   |
+| 0.5451        | 2.2857 | 2000 | 1.2895          | 0.6556   |
+| 0.4287        | 2.8571 | 2500 | 1.2736          | 0.6644   |
+| 0.2554        | 3.4286 | 3000 | 1.3801          | 0.6767   |
+| 0.2265        | 4.0    | 3500 | 1.4924          | 0.6656   |
+| 0.0738        | 4.5714 | 4000 | 1.6321          | 0.68     |
+| 0.0761        | 5.1429 | 4500 | 1.6676          | 0.6767   |
+| 0.0251        | 5.7143 | 5000 | 1.6911          | 0.7056   |
+| 0.0147        | 6.2857 | 5500 | 1.7312          | 0.7      |
+| 0.0051        | 6.8571 | 6000 | 1.7282          | 0.6922   |
+| 0.0028        | 7.4286 | 6500 | 1.7679          | 0.6967   |
+| 0.0017        | 8.0    | 7000 | 1.7642          | 0.6989   |
+
+
+### Framework versions
+
+- Transformers 4.40.0
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.0
+- Tokenizers 0.19.1

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