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# vit-msn-small-wbc-classifier-cells-separated-dataset-no-agregates-10

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: 0.1504
- Accuracy: 0.9463

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.3353        | 0.9937 | 118  | 0.2299          | 0.9214   |
| 0.2884        | 1.9958 | 237  | 0.2378          | 0.9172   |
| 0.2487        | 2.9979 | 356  | 0.1871          | 0.9360   |
| 0.2347        | 4.0    | 475  | 0.1920          | 0.9328   |
| 0.2343        | 4.9937 | 593  | 0.1674          | 0.9405   |
| 0.2285        | 5.9958 | 712  | 0.1642          | 0.9426   |
| 0.2079        | 6.9979 | 831  | 0.1836          | 0.9344   |
| 0.2155        | 8.0    | 950  | 0.1661          | 0.9442   |
| 0.1954        | 8.9937 | 1068 | 0.1504          | 0.9463   |
| 0.1763        | 9.9368 | 1180 | 0.1588          | 0.9450   |


### Framework versions

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

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