metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swinv2-large-patch4-window12to16-192to256-22kto1k-ft-finetuned-eurosat-50
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: Augmented-Final
split: train
args: Augmented-Final
metrics:
- name: Accuracy
type: accuracy
value: 0.9753340184994861
swinv2-large-patch4-window12to16-192to256-22kto1k-ft-finetuned-eurosat-50
This model is a fine-tuned version of microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0909
- Accuracy: 0.9753
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-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.9
- num_epochs: 12
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.0236 | 1.0 | 122 | 1.9878 | 0.1305 |
| 1.88 | 2.0 | 244 | 1.7957 | 0.2867 |
| 1.5421 | 3.0 | 366 | 1.3813 | 0.5149 |
| 0.9489 | 4.0 | 488 | 0.9015 | 0.7030 |
| 0.8734 | 5.0 | 610 | 0.6616 | 0.7667 |
| 0.6562 | 6.0 | 732 | 0.5095 | 0.8140 |
| 0.5788 | 7.0 | 854 | 0.4036 | 0.8520 |
| 0.6737 | 8.0 | 976 | 0.3157 | 0.8921 |
| 0.4687 | 9.0 | 1098 | 0.2146 | 0.9281 |
| 0.3775 | 10.0 | 1220 | 0.2020 | 0.9353 |
| 0.3226 | 11.0 | 1342 | 0.1549 | 0.9558 |
| 0.2452 | 12.0 | 1464 | 0.0909 | 0.9753 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3