
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# vit-base-patch16-224-in21k-lcbsi

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 None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0690
- Accuracy: 0.9853

## 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: 0.001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5933        | 0.98  | 27   | 0.1754          | 0.9587   |
| 0.2672        | 1.98  | 54   | 0.1286          | 0.964    |
| 0.153         | 2.98  | 81   | 0.1375          | 0.9627   |
| 0.0838        | 3.98  | 108  | 0.1100          | 0.9733   |
| 0.0457        | 4.98  | 135  | 0.1678          | 0.952    |
| 0.0366        | 5.98  | 162  | 0.0744          | 0.9813   |
| 0.0108        | 6.98  | 189  | 0.0834          | 0.9827   |
| 0.0075        | 7.98  | 216  | 0.0690          | 0.9853   |
| 0.0051        | 8.98  | 243  | 0.0739          | 0.984    |
| 0.0028        | 9.98  | 270  | 0.0731          | 0.984    |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2

basophil eosinophil lymphocyte monocyte neutrophil