Final model push

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
+tags:
+- generated_from_trainer
+datasets:
+- arrow
+metrics:
+- accuracy
+model-index:
+- name: fabric_classifier
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: arrow
+      type: arrow
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.498
+---
+
+<!-- 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. -->
+
+# fabric_classifier
+
+This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the arrow dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.0291
+- Accuracy: 0.498
+- F1 Macro: 0.0820
+- F1 Micro: 0.498
+
+## 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: 3e-05
+- train_batch_size: 8
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 5
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Micro |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
+| 2.567         | 1.0   | 250  | 2.4475          | 0.382    | 0.0384   | 0.382    |
+| 2.2146        | 2.0   | 500  | 2.2285          | 0.406    | 0.0499   | 0.406    |
+| 1.9667        | 3.0   | 750  | 2.0838          | 0.474    | 0.0696   | 0.474    |
+| 1.7922        | 4.0   | 1000 | 2.0460          | 0.49     | 0.0841   | 0.49     |
+| 1.5825        | 5.0   | 1250 | 2.0291          | 0.498    | 0.0820   | 0.498    |
+
+
+### Framework versions
+
+- Transformers 4.57.0
+- Pytorch 2.8.0+cu126
+- Datasets 4.0.0
+- Tokenizers 0.22.1