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---
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
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