metadata
license: apache-2.0
base_model: microsoft/swinv2-tiny-patch4-window8-256
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swinv2-tiny-patch4-window8-256-finalterm
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: 0.9
swinv2-tiny-patch4-window8-256-finalterm
This model is a fine-tuned version of microsoft/swinv2-tiny-patch4-window8-256 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.2805
- Accuracy: 0.9
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: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.3578 | 1.0 | 10 | 1.2444 | 0.475 |
| 1.1054 | 2.0 | 20 | 0.9180 | 0.6531 |
| 0.8485 | 3.0 | 30 | 0.6632 | 0.725 |
| 0.674 | 4.0 | 40 | 0.4736 | 0.7969 |
| 0.5968 | 5.0 | 50 | 0.4341 | 0.8125 |
| 0.508 | 6.0 | 60 | 0.5391 | 0.8187 |
| 0.4852 | 7.0 | 70 | 0.3906 | 0.8344 |
| 0.4354 | 8.0 | 80 | 0.3257 | 0.8656 |
| 0.4165 | 9.0 | 90 | 0.3478 | 0.8656 |
| 0.4385 | 10.0 | 100 | 0.3114 | 0.8781 |
| 0.4156 | 11.0 | 110 | 0.3461 | 0.8781 |
| 0.4055 | 12.0 | 120 | 0.3108 | 0.8844 |
| 0.4282 | 13.0 | 130 | 0.2916 | 0.8875 |
| 0.3546 | 14.0 | 140 | 0.2972 | 0.9 |
| 0.3608 | 15.0 | 150 | 0.3428 | 0.8688 |
| 0.369 | 16.0 | 160 | 0.2885 | 0.8969 |
| 0.3525 | 17.0 | 170 | 0.2861 | 0.9 |
| 0.338 | 18.0 | 180 | 0.2832 | 0.9062 |
| 0.3633 | 19.0 | 190 | 0.2797 | 0.9031 |
| 0.3712 | 20.0 | 200 | 0.2805 | 0.9 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1