---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: beit-large-patch16-224-finetuned-BreastCancer-Classification-BreakHis-AH-60-20-20
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: Splitted-Resized
      split: train
      args: Splitted-Resized
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9938708156529938
---

<!-- 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. -->

# beit-large-patch16-224-finetuned-BreastCancer-Classification-BreakHis-AH-60-20-20

This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0275
- Accuracy: 0.9939

## 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-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.9
- num_epochs: 12

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.46          | 1.0   | 199  | 0.3950          | 0.8482   |
| 0.2048        | 2.0   | 398  | 0.1886          | 0.9189   |
| 0.182         | 3.0   | 597  | 0.1382          | 0.9481   |
| 0.0826        | 4.0   | 796  | 0.0760          | 0.9694   |
| 0.0886        | 5.0   | 995  | 0.0600          | 0.9788   |
| 0.0896        | 6.0   | 1194 | 0.0523          | 0.9802   |
| 0.0774        | 7.0   | 1393 | 0.0482          | 0.9826   |
| 0.0876        | 8.0   | 1592 | 0.0289          | 0.9877   |
| 0.1105        | 9.0   | 1791 | 0.0580          | 0.9821   |
| 0.0289        | 10.0  | 1990 | 0.0294          | 0.9925   |
| 0.0594        | 11.0  | 2189 | 0.0331          | 0.9906   |
| 0.0011        | 12.0  | 2388 | 0.0275          | 0.9939   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3