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# my_isl_model

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 imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9092
- Accuracy: 0.7284

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.1292        | 0.96  | 11   | 3.0256          | 0.2593   |
| 2.9426        | 2.0   | 23   | 2.7796          | 0.2716   |
| 2.706         | 2.96  | 34   | 2.5462          | 0.4321   |
| 2.5389        | 4.0   | 46   | 2.4454          | 0.4568   |
| 2.3638        | 4.96  | 57   | 2.2169          | 0.6914   |
| 2.1862        | 6.0   | 69   | 2.1349          | 0.6296   |
| 2.0459        | 6.96  | 80   | 2.1135          | 0.6049   |
| 1.9912        | 8.0   | 92   | 1.9757          | 0.7531   |
| 1.9504        | 8.96  | 103  | 1.9073          | 0.7407   |
| 1.942         | 9.57  | 110  | 1.9092          | 0.7284   |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

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