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# test_model_8

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: 1.8797
- F1 Macro: 0.0598
- F1 Micro: 0.2121
- F1 Weighted: 0.0845
- Precision Macro: 0.1723
- Precision Micro: 0.2121
- Precision Weighted: 0.2316
- Recall Macro: 0.1486
- Recall Micro: 0.2121
- Recall Weighted: 0.2121
- Accuracy: 0.2121

## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Micro | F1 Weighted | Precision Macro | Precision Micro | Precision Weighted | Recall Macro | Recall Micro | Recall Weighted | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|:---------------:|:---------------:|:------------------:|:------------:|:------------:|:---------------:|:--------:|
| 1.9439        | 0.8   | 3    | 1.9065          | 0.0541   | 0.1894   | 0.0764      | 0.0625          | 0.1894          | 0.0857             | 0.1327       | 0.1894       | 0.1894          | 0.1894   |
| 1.9049        | 1.8   | 6    | 1.8820          | 0.0578   | 0.2045   | 0.0818      | 0.0501          | 0.2045          | 0.0696             | 0.1433       | 0.2045       | 0.2045          | 0.2045   |
| 2.3436        | 2.8   | 9    | 1.8773          | 0.0738   | 0.1894   | 0.1022      | 0.0567          | 0.1894          | 0.0780             | 0.1348       | 0.1894       | 0.1894          | 0.1894   |


### Framework versions

- Transformers 4.48.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0

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