vit-msn-small-wbc-classifier-0316-cleaned-dataset-10
This model is a fine-tuned version of facebook/vit-msn-small on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.3538
- Accuracy: 0.8935
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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 25
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.5193 | 1.0 | 16 | 0.6823 | 0.7945 |
| 0.5339 | 2.0 | 32 | 0.4553 | 0.8438 |
| 0.4778 | 3.0 | 48 | 0.4525 | 0.8478 |
| 0.4253 | 4.0 | 64 | 0.4077 | 0.8473 |
| 0.4086 | 5.0 | 80 | 0.4218 | 0.8575 |
| 0.3673 | 6.0 | 96 | 0.4002 | 0.8693 |
| 0.3275 | 7.0 | 112 | 0.3302 | 0.8773 |
| 0.3231 | 8.0 | 128 | 0.3672 | 0.8803 |
| 0.302 | 9.0 | 144 | 0.3363 | 0.8900 |
| 0.3122 | 10.0 | 160 | 0.3284 | 0.8843 |
| 0.2686 | 11.0 | 176 | 0.3317 | 0.8874 |
| 0.2786 | 12.0 | 192 | 0.3660 | 0.8883 |
| 0.2338 | 13.0 | 208 | 0.3520 | 0.8834 |
| 0.2466 | 14.0 | 224 | 0.3414 | 0.8896 |
| 0.2296 | 15.0 | 240 | 0.3531 | 0.8874 |
| 0.1961 | 16.0 | 256 | 0.3844 | 0.8847 |
| 0.2056 | 17.0 | 272 | 0.3705 | 0.8900 |
| 0.197 | 18.0 | 288 | 0.3538 | 0.8935 |
| 0.1748 | 19.0 | 304 | 0.3717 | 0.8887 |
| 0.1807 | 20.0 | 320 | 0.4075 | 0.8843 |
| 0.177 | 21.0 | 336 | 0.3881 | 0.8830 |
| 0.1433 | 22.0 | 352 | 0.4014 | 0.8856 |
| 0.1522 | 23.0 | 368 | 0.3918 | 0.8874 |
| 0.1322 | 24.0 | 384 | 0.4199 | 0.8905 |
| 0.1396 | 25.0 | 400 | 0.4142 | 0.8896 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1