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# axl-tif-images-v1

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: 0.1686
- Accuracy: 0.9583
- F1: 0.9576
- Precision: 0.9608
- Recall: 0.9583

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.5574        | 1.0   | 24   | 0.3268          | 0.9583   | 0.9576 | 0.9608    | 0.9583 |
| 0.2038        | 2.0   | 48   | 0.1576          | 0.9583   | 0.9576 | 0.9608    | 0.9583 |
| 0.0568        | 3.0   | 72   | 0.3077          | 0.9167   | 0.9132 | 0.9259    | 0.9167 |
| 0.0661        | 4.0   | 96   | 0.1585          | 0.9583   | 0.9589 | 0.9630    | 0.9583 |
| 0.0648        | 5.0   | 120  | 0.0147          | 1.0      | 1.0    | 1.0       | 1.0    |
| 0.0185        | 6.0   | 144  | 0.0130          | 1.0      | 1.0    | 1.0       | 1.0    |
| 0.0113        | 7.0   | 168  | 0.0113          | 1.0      | 1.0    | 1.0       | 1.0    |
| 0.0463        | 8.0   | 192  | 0.1764          | 0.9583   | 0.9589 | 0.9630    | 0.9583 |
| 0.1297        | 9.0   | 216  | 0.0098          | 1.0      | 1.0    | 1.0       | 1.0    |
| 0.0763        | 10.0  | 240  | 0.1686          | 0.9583   | 0.9576 | 0.9608    | 0.9583 |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.7.0+cu128
- Datasets 3.6.0
- Tokenizers 0.21.1

good bad