|
--- |
|
license: apache-2.0 |
|
base_model: Yogesh1p/swin-tiny-patch4-window7-224-finetuned-cp1 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- imagefolder |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: swin-tiny-patch4-window7-224-finetuned-cp1 |
|
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: 0.8666666666666667 |
|
--- |
|
|
|
<!-- 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-cp1 |
|
|
|
This model is a fine-tuned version of [Yogesh1p/swin-tiny-patch4-window7-224-finetuned-cp1](https://huggingface.co/Yogesh1p/swin-tiny-patch4-window7-224-finetuned-cp1) on the imagefolder dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3628 |
|
- Accuracy: 0.8667 |
|
|
|
## 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: 30 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| No log | 0.92 | 3 | 0.4305 | 0.8222 | |
|
| No log | 1.85 | 6 | 0.4510 | 0.8 | |
|
| No log | 2.77 | 9 | 0.4329 | 0.7778 | |
|
| 0.3489 | 4.0 | 13 | 0.4965 | 0.7778 | |
|
| 0.3489 | 4.92 | 16 | 0.4247 | 0.8 | |
|
| 0.3489 | 5.85 | 19 | 0.3559 | 0.8444 | |
|
| 0.2872 | 6.77 | 22 | 0.3628 | 0.8667 | |
|
| 0.2872 | 8.0 | 26 | 0.3511 | 0.8667 | |
|
| 0.2872 | 8.92 | 29 | 0.3538 | 0.8667 | |
|
| 0.3071 | 9.85 | 32 | 0.3644 | 0.8222 | |
|
| 0.3071 | 10.77 | 35 | 0.3860 | 0.8222 | |
|
| 0.3071 | 12.0 | 39 | 0.5917 | 0.8 | |
|
| 0.2765 | 12.92 | 42 | 0.5149 | 0.7778 | |
|
| 0.2765 | 13.85 | 45 | 0.5605 | 0.7556 | |
|
| 0.2765 | 14.77 | 48 | 0.4737 | 0.8 | |
|
| 0.2637 | 16.0 | 52 | 0.4109 | 0.8444 | |
|
| 0.2637 | 16.92 | 55 | 0.3584 | 0.8222 | |
|
| 0.2637 | 17.85 | 58 | 0.3771 | 0.8222 | |
|
| 0.2082 | 18.77 | 61 | 0.4406 | 0.8222 | |
|
| 0.2082 | 20.0 | 65 | 0.3592 | 0.8222 | |
|
| 0.2082 | 20.92 | 68 | 0.3302 | 0.8667 | |
|
| 0.1944 | 21.85 | 71 | 0.3206 | 0.8444 | |
|
| 0.1944 | 22.77 | 74 | 0.3215 | 0.8667 | |
|
| 0.1944 | 24.0 | 78 | 0.3209 | 0.8667 | |
|
| 0.2144 | 24.92 | 81 | 0.3327 | 0.8444 | |
|
| 0.2144 | 25.85 | 84 | 0.3506 | 0.8444 | |
|
| 0.2144 | 26.77 | 87 | 0.3545 | 0.8444 | |
|
| 0.1754 | 27.69 | 90 | 0.3494 | 0.8444 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.2 |
|
- Pytorch 2.1.0+cu118 |
|
- Datasets 2.15.0 |
|
- Tokenizers 0.15.0 |
|
|
