|
--- |
|
license: apache-2.0 |
|
base_model: microsoft/swinv2-tiny-patch4-window8-256 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- imagefolder |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: msi-swinv2-tiny |
|
results: |
|
- task: |
|
name: Image Classification |
|
type: image-classification |
|
dataset: |
|
name: imagefolder |
|
type: imagefolder |
|
config: default |
|
split: validation |
|
args: default |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.6273762929829466 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# msi-swinv2-tiny |
|
|
|
This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on the imagefolder dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.5764 |
|
- Accuracy: 0.6274 |
|
|
|
## 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: 1e-05 |
|
- train_batch_size: 16 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 64 |
|
- 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 | |
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
|
| 0.4392 | 1.0 | 2015 | 0.7935 | 0.6100 | |
|
| 0.3266 | 2.0 | 4031 | 0.9694 | 0.6132 | |
|
| 0.2673 | 3.0 | 6047 | 1.2037 | 0.6114 | |
|
| 0.2222 | 4.0 | 8063 | 1.3734 | 0.6097 | |
|
| 0.1922 | 5.0 | 10078 | 1.3308 | 0.6235 | |
|
| 0.1716 | 6.0 | 12094 | 1.4758 | 0.6136 | |
|
| 0.1742 | 7.0 | 14110 | 1.4332 | 0.6274 | |
|
| 0.1653 | 8.0 | 16126 | 1.4940 | 0.6247 | |
|
| 0.1429 | 9.0 | 18141 | 1.6058 | 0.6236 | |
|
| 0.1546 | 10.0 | 20150 | 1.5764 | 0.6274 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.2 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 2.15.0 |
|
- Tokenizers 0.15.0 |
|
|
