|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- imagefolder |
|
metrics: |
|
- accuracy |
|
- precision |
|
model-index: |
|
- name: swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_08 |
|
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: 0.9591516103692066 |
|
- name: Precision |
|
type: precision |
|
value: 0.9627515459909033 |
|
--- |
|
|
|
<!-- 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-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_08 |
|
|
|
This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224-in22k](https://huggingface.co/microsoft/swin-base-patch4-window7-224-in22k) on the imagefolder dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1210 |
|
- Accuracy: 0.9592 |
|
- F1 Score: 0.9600 |
|
- Precision: 0.9628 |
|
|
|
## 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: 100 |
|
- eval_batch_size: 100 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 400 |
|
- 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 | F1 Score | Precision | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:| |
|
| 1.2882 | 0.99 | 19 | 0.5469 | 0.7962 | 0.7863 | 0.8077 | |
|
| 0.3491 | 1.97 | 38 | 0.3030 | 0.8861 | 0.8878 | 0.8981 | |
|
| 0.1791 | 2.96 | 57 | 0.2077 | 0.9211 | 0.9229 | 0.9307 | |
|
| 0.122 | 4.0 | 77 | 0.2007 | 0.9254 | 0.9272 | 0.9369 | |
|
| 0.0671 | 4.99 | 96 | 0.2073 | 0.9269 | 0.9294 | 0.9401 | |
|
| 0.0474 | 5.97 | 115 | 0.1384 | 0.9482 | 0.9494 | 0.9547 | |
|
| 0.032 | 6.96 | 134 | 0.1683 | 0.9430 | 0.9447 | 0.9511 | |
|
| 0.0225 | 8.0 | 154 | 0.1101 | 0.9650 | 0.9657 | 0.9671 | |
|
| 0.0193 | 8.99 | 173 | 0.1372 | 0.9533 | 0.9544 | 0.9585 | |
|
| 0.0193 | 9.87 | 190 | 0.1210 | 0.9592 | 0.9600 | 0.9628 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.29.2 |
|
- Pytorch 2.0.1+cu117 |
|
- Datasets 2.12.0 |
|
- Tokenizers 0.13.3 |
|
|
