|
--- |
|
license: apache-2.0 |
|
base_model: microsoft/swin-tiny-patch4-window7-224 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- imagefolder |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: swin-tiny-patch4-window7-224-finetuned-fish |
|
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: 0.6666666666666666 |
|
--- |
|
|
|
<!-- 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-tiny-patch4-window7-224-finetuned-fish |
|
|
|
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: 0.8536 |
|
- Accuracy: 0.6667 |
|
|
|
## 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: 32 |
|
- eval_batch_size: 32 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 128 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 25 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| No log | 1.0 | 1 | 1.9028 | 0.3333 | |
|
| No log | 2.0 | 2 | 1.8803 | 0.3333 | |
|
| No log | 3.0 | 3 | 1.8603 | 0.3333 | |
|
| No log | 4.0 | 4 | 1.8293 | 0.3333 | |
|
| No log | 5.0 | 5 | 1.8093 | 0.3333 | |
|
| No log | 6.0 | 6 | 1.7682 | 0.3333 | |
|
| No log | 7.0 | 7 | 1.7140 | 0.3333 | |
|
| No log | 8.0 | 8 | 1.6566 | 0.3333 | |
|
| No log | 9.0 | 9 | 1.6020 | 0.3333 | |
|
| 0.8416 | 10.0 | 10 | 1.5466 | 0.3333 | |
|
| 0.8416 | 11.0 | 11 | 1.4709 | 0.3333 | |
|
| 0.8416 | 12.0 | 12 | 1.3894 | 0.3333 | |
|
| 0.8416 | 13.0 | 13 | 1.3049 | 0.5 | |
|
| 0.8416 | 14.0 | 14 | 1.2186 | 0.6667 | |
|
| 0.8416 | 15.0 | 15 | 1.1344 | 0.6667 | |
|
| 0.8416 | 16.0 | 16 | 1.0706 | 0.6667 | |
|
| 0.8416 | 17.0 | 17 | 1.0184 | 0.6667 | |
|
| 0.8416 | 18.0 | 18 | 0.9807 | 0.6667 | |
|
| 0.8416 | 19.0 | 19 | 0.9455 | 0.6667 | |
|
| 0.433 | 20.0 | 20 | 0.9182 | 0.6667 | |
|
| 0.433 | 21.0 | 21 | 0.8942 | 0.6667 | |
|
| 0.433 | 22.0 | 22 | 0.8766 | 0.6667 | |
|
| 0.433 | 23.0 | 23 | 0.8654 | 0.6667 | |
|
| 0.433 | 24.0 | 24 | 0.8578 | 0.6667 | |
|
| 0.433 | 25.0 | 25 | 0.8536 | 0.6667 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.40.1 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.19.0 |
|
- Tokenizers 0.19.1 |
|
|
