swinv2-tiny-patch4-window16-256-finetuned-tekno24
This model is a fine-tuned version of microsoft/swinv2-tiny-patch4-window16-256 on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2871
- Accuracy: 0.4224
- F1: 0.3135
- Precision: 0.4313
- Recall: 0.4224
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: 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
- mixed_precision_training: Native AMP
Training results
| Training Loss |
Epoch |
Step |
Validation Loss |
Accuracy |
F1 |
Precision |
Recall |
| 1.3705 |
0.9963 |
68 |
1.3584 |
0.3563 |
0.2590 |
0.2886 |
0.3563 |
| 1.3515 |
1.9927 |
136 |
1.3392 |
0.3921 |
0.2606 |
0.3925 |
0.3921 |
| 1.3498 |
2.9890 |
204 |
1.3301 |
0.3912 |
0.2501 |
0.4247 |
0.3912 |
| 1.3351 |
4.0 |
273 |
1.3225 |
0.3930 |
0.2452 |
0.5371 |
0.3930 |
| 1.3212 |
4.9963 |
341 |
1.3128 |
0.3949 |
0.2556 |
0.4641 |
0.3949 |
| 1.3316 |
5.9927 |
409 |
1.3052 |
0.4004 |
0.2723 |
0.4129 |
0.4004 |
| 1.3269 |
6.9890 |
477 |
1.2980 |
0.4068 |
0.2850 |
0.4305 |
0.4068 |
| 1.3034 |
8.0 |
546 |
1.2927 |
0.4123 |
0.2924 |
0.4448 |
0.4123 |
| 1.3165 |
8.9963 |
614 |
1.2884 |
0.4215 |
0.3096 |
0.4453 |
0.4215 |
| 1.3306 |
9.9634 |
680 |
1.2871 |
0.4224 |
0.3135 |
0.4313 |
0.4224 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
