|
--- |
|
license: apache-2.0 |
|
base_model: microsoft/swin-tiny-patch4-window7-224 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- imagefolder |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: segformer-class-classWeights-augmentation |
|
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: 0.896551724137931 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# segformer-class-classWeights-augmentation |
|
|
|
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: 0.4768 |
|
- Accuracy: 0.8966 |
|
|
|
## 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: 128 |
|
- eval_batch_size: 128 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 512 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 20 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| No log | 1.0 | 1 | 1.0387 | 0.3103 | |
|
| No log | 2.0 | 3 | 1.0144 | 0.6552 | |
|
| No log | 3.0 | 5 | 0.9570 | 0.7241 | |
|
| No log | 4.0 | 6 | 0.9075 | 0.6552 | |
|
| No log | 5.0 | 7 | 0.8455 | 0.7241 | |
|
| No log | 6.0 | 9 | 0.7622 | 0.7931 | |
|
| 0.4555 | 7.0 | 11 | 0.7067 | 0.7931 | |
|
| 0.4555 | 8.0 | 12 | 0.6745 | 0.8276 | |
|
| 0.4555 | 9.0 | 13 | 0.6108 | 0.8621 | |
|
| 0.4555 | 10.0 | 15 | 0.5319 | 0.8966 | |
|
| 0.4555 | 11.0 | 17 | 0.4943 | 0.8966 | |
|
| 0.4555 | 12.0 | 18 | 0.4896 | 0.8966 | |
|
| 0.4555 | 13.0 | 19 | 0.4820 | 0.8966 | |
|
| 0.2224 | 13.33 | 20 | 0.4768 | 0.8966 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.31.0 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 2.13.1 |
|
- Tokenizers 0.13.3 |
|
|
