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# vit-msn-small-lateral_flow_ivalidation_green_test

This model is a fine-tuned version of [facebook/vit-msn-small](https://huggingface.co/facebook/vit-msn-small) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2823
- Accuracy: 0.8810

## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| No log        | 0.9231 | 6    | 0.4106          | 0.7918   |
| 0.5328        | 2.0    | 13   | 0.2823          | 0.8810   |
| 0.5328        | 2.9231 | 19   | 0.3051          | 0.8587   |
| 0.4244        | 4.0    | 26   | 0.2913          | 0.8996   |
| 0.3755        | 4.9231 | 32   | 0.2841          | 0.9052   |
| 0.3755        | 6.0    | 39   | 0.3204          | 0.8829   |
| 0.3569        | 6.9231 | 45   | 0.2982          | 0.8810   |
| 0.3157        | 8.0    | 52   | 0.3317          | 0.8643   |
| 0.3157        | 8.9231 | 58   | 0.5731          | 0.7249   |
| 0.3177        | 9.2308 | 60   | 0.5725          | 0.7305   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1

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