|
--- |
|
library_name: transformers |
|
license: apache-2.0 |
|
base_model: microsoft/swin-tiny-patch4-window7-224 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- imagefolder |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: swin-tiny-patch4-window7-224-finetuned-papsmear |
|
results: |
|
- task: |
|
name: Image Classification |
|
type: image-classification |
|
dataset: |
|
name: imagefolder |
|
type: imagefolder |
|
config: default |
|
split: train |
|
args: default |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.9044117647058824 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# swin-tiny-patch4-window7-224-finetuned-papsmear |
|
|
|
This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2027 |
|
- Accuracy: 0.9044 |
|
|
|
## 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: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- 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: 0.1 |
|
- num_epochs: 15 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-------:|:----:|:---------------:|:--------:| |
|
| 1.4844 | 0.9935 | 38 | 1.4298 | 0.4118 | |
|
| 0.8905 | 1.9869 | 76 | 0.8110 | 0.6544 | |
|
| 0.9097 | 2.9804 | 114 | 0.7109 | 0.7132 | |
|
| 0.6238 | 4.0 | 153 | 0.9197 | 0.6544 | |
|
| 0.4456 | 4.9935 | 191 | 0.4652 | 0.8015 | |
|
| 0.4394 | 5.9869 | 229 | 0.5188 | 0.8015 | |
|
| 0.3156 | 6.9804 | 267 | 0.3447 | 0.8529 | |
|
| 0.2212 | 8.0 | 306 | 0.3509 | 0.8382 | |
|
| 0.2402 | 8.9935 | 344 | 0.3939 | 0.8235 | |
|
| 0.1733 | 9.9869 | 382 | 0.2444 | 0.8897 | |
|
| 0.1953 | 10.9804 | 420 | 0.2639 | 0.8676 | |
|
| 0.1363 | 12.0 | 459 | 0.2645 | 0.8824 | |
|
| 0.1234 | 12.9935 | 497 | 0.2027 | 0.9044 | |
|
| 0.1282 | 13.9869 | 535 | 0.2027 | 0.9044 | |
|
| 0.1036 | 14.9020 | 570 | 0.2026 | 0.8897 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.44.2 |
|
- Pytorch 2.4.0+cu121 |
|
- Datasets 3.0.0 |
|
- Tokenizers 0.19.1 |
|
|
