msi-vit-small-1218-2
This model is a fine-tuned version of WinKawaks/vit-small-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.3372
- Accuracy: 0.6164
- F1: 0.3276
- Precision: 0.6841
- Recall: 0.2154
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: 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.4367 | 1.0 | 1008 | 0.6603 | 0.6572 | 0.5313 | 0.6530 | 0.4478 |
| 0.2161 | 2.0 | 2016 | 0.8021 | 0.6329 | 0.4989 | 0.6118 | 0.4211 |
| 0.169 | 3.0 | 3024 | 1.4062 | 0.6010 | 0.2653 | 0.6592 | 0.1661 |
| 0.1543 | 4.0 | 4032 | 1.1498 | 0.6259 | 0.3670 | 0.6903 | 0.2499 |
| 0.1534 | 5.0 | 5040 | 1.5067 | 0.6208 | 0.3519 | 0.6808 | 0.2373 |
| 0.1596 | 6.0 | 6048 | 0.8837 | 0.6504 | 0.6505 | 0.5744 | 0.7498 |
| 0.1504 | 7.0 | 7056 | 1.0030 | 0.6302 | 0.4192 | 0.6580 | 0.3075 |
| 0.1795 | 8.0 | 8064 | 1.3908 | 0.5953 | 0.2950 | 0.6041 | 0.1952 |
| 0.1636 | 9.0 | 9072 | 1.1040 | 0.6290 | 0.4619 | 0.6230 | 0.3671 |
| 0.1629 | 10.0 | 10080 | 1.3372 | 0.6164 | 0.3276 | 0.6841 | 0.2154 |
Framework versions
- Transformers 4.36.0
- Pytorch 2.0.1+cu117
- Datasets 2.15.0
- Tokenizers 0.15.0