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# asl_aplhabet_img_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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9586
- Accuracy: 0.2692

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 26   | 3.2666          | 0.0385   |
| No log        | 2.0   | 52   | 3.2701          | 0.0385   |
| No log        | 3.0   | 78   | 3.2713          | 0.0288   |
| No log        | 4.0   | 104  | 3.2701          | 0.0769   |
| No log        | 5.0   | 130  | 3.2584          | 0.0385   |
| No log        | 6.0   | 156  | 3.2537          | 0.0577   |
| No log        | 7.0   | 182  | 3.2402          | 0.0577   |
| No log        | 8.0   | 208  | 3.2364          | 0.0577   |
| No log        | 9.0   | 234  | 3.2055          | 0.0769   |
| No log        | 10.0  | 260  | 3.1794          | 0.0769   |
| No log        | 11.0  | 286  | 3.1851          | 0.1346   |
| No log        | 12.0  | 312  | 3.1811          | 0.1058   |
| No log        | 13.0  | 338  | 3.1594          | 0.1346   |
| No log        | 14.0  | 364  | 3.1269          | 0.1635   |
| No log        | 15.0  | 390  | 3.1082          | 0.125    |
| No log        | 16.0  | 416  | 3.1019          | 0.2019   |
| No log        | 17.0  | 442  | 3.0886          | 0.2019   |
| No log        | 18.0  | 468  | 3.0599          | 0.2115   |
| No log        | 19.0  | 494  | 3.0622          | 0.1731   |
| 3.0197        | 20.0  | 520  | 3.0474          | 0.1538   |
| 3.0197        | 21.0  | 546  | 3.0245          | 0.2115   |
| 3.0197        | 22.0  | 572  | 3.0386          | 0.1923   |
| 3.0197        | 23.0  | 598  | 3.0236          | 0.1923   |
| 3.0197        | 24.0  | 624  | 3.0201          | 0.1923   |
| 3.0197        | 25.0  | 650  | 3.0056          | 0.2212   |
| 3.0197        | 26.0  | 676  | 2.9649          | 0.25     |
| 3.0197        | 27.0  | 702  | 2.9900          | 0.2212   |
| 3.0197        | 28.0  | 728  | 2.9823          | 0.2308   |
| 3.0197        | 29.0  | 754  | 2.9782          | 0.2115   |
| 3.0197        | 30.0  | 780  | 3.0136          | 0.1635   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2

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