|
--- |
|
license: apache-2.0 |
|
base_model: google/vit-large-patch32-224-in21k |
|
tags: |
|
- image-classification |
|
- generated_from_trainer |
|
datasets: |
|
- imagefolder |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: vit-large-brain-xray |
|
results: |
|
- task: |
|
name: Image Classification |
|
type: image-classification |
|
dataset: |
|
name: sartajbhuvaji/Brain-Tumor-Classification |
|
type: imagefolder |
|
config: default |
|
split: Testing |
|
args: default |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.7741116751269036 |
|
--- |
|
|
|
<!-- 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-large-brain-xray |
|
|
|
This model is a fine-tuned version of [google/vit-large-patch32-224-in21k](https://huggingface.co/google/vit-large-patch32-224-in21k) on the sartajbhuvaji/Brain-Tumor-Classification dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.9050 |
|
- Accuracy: 0.7741 |
|
|
|
## 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: 0.0002 |
|
- train_batch_size: 16 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 4 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:------:|:----:|:---------------:|:--------:| |
|
| 0.352 | 0.5556 | 100 | 1.2267 | 0.6294 | |
|
| 0.1612 | 1.1111 | 200 | 1.0895 | 0.7538 | |
|
| 0.0473 | 1.6667 | 300 | 0.9050 | 0.7741 | |
|
| 0.0525 | 2.2222 | 400 | 1.0663 | 0.7690 | |
|
| 0.0123 | 2.7778 | 500 | 1.2450 | 0.7462 | |
|
| 0.0066 | 3.3333 | 600 | 1.1283 | 0.7817 | |
|
| 0.0126 | 3.8889 | 700 | 1.1717 | 0.7843 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.40.1 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.19.0 |
|
- Tokenizers 0.19.1 |
|
|