|
--- |
|
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_06 |
|
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: 0.9225512528473804 |
|
- name: Precision |
|
type: precision |
|
value: 0.9214370287637926 |
|
--- |
|
|
|
<!-- 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_06 |
|
|
|
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: 0.2384 |
|
- Accuracy: 0.9226 |
|
- F1 Score: 0.9210 |
|
- Precision: 0.9214 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:| |
|
| 1.3082 | 0.98 | 13 | 0.7669 | 0.7819 | 0.7689 | 0.7723 | |
|
| 0.5415 | 1.96 | 26 | 0.3100 | 0.8867 | 0.8812 | 0.8816 | |
|
| 0.279 | 2.94 | 39 | 0.2901 | 0.8992 | 0.8967 | 0.8961 | |
|
| 0.1563 | 4.0 | 53 | 0.2655 | 0.9089 | 0.9078 | 0.9084 | |
|
| 0.1304 | 4.98 | 66 | 0.2971 | 0.8964 | 0.8935 | 0.8958 | |
|
| 0.1058 | 5.96 | 79 | 0.2358 | 0.9243 | 0.9218 | 0.9224 | |
|
| 0.0971 | 6.94 | 92 | 0.2298 | 0.9260 | 0.9245 | 0.9258 | |
|
| 0.079 | 8.0 | 106 | 0.2468 | 0.9134 | 0.9123 | 0.9125 | |
|
| 0.0638 | 8.98 | 119 | 0.2534 | 0.9112 | 0.9097 | 0.9101 | |
|
| 0.0538 | 9.81 | 130 | 0.2384 | 0.9226 | 0.9210 | 0.9214 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.29.2 |
|
- Pytorch 2.0.1+cu117 |
|
- Datasets 2.12.0 |
|
- Tokenizers 0.13.3 |
|
|
