vit-base-patch16-224-finetuned-barkley
This model is a fine-tuned version of google/vit-base-patch16-224 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0036
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
- Accuracy: 1.0
- Top1 Accuracy: 1.0
- Error Rate: 0.0
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: 0.0005
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 0.1
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | Top1 Accuracy | Error Rate |
|---|---|---|---|---|---|---|---|---|---|
| 1.6093 | 1.0 | 38 | 1.4340 | 0.4769 | 0.4342 | 0.4066 | 0.4149 | 0.4342 | 0.5851 |
| 1.2908 | 2.0 | 76 | 1.1747 | 0.6587 | 0.6118 | 0.6160 | 0.6161 | 0.6118 | 0.3839 |
| 1.0409 | 3.0 | 114 | 0.9174 | 0.7382 | 0.7303 | 0.7293 | 0.7425 | 0.7303 | 0.2575 |
| 0.781 | 4.0 | 152 | 0.6528 | 0.8632 | 0.8618 | 0.8622 | 0.8650 | 0.8618 | 0.1350 |
| 0.5429 | 5.0 | 190 | 0.4112 | 0.9417 | 0.9408 | 0.9405 | 0.9443 | 0.9408 | 0.0557 |
| 0.328 | 6.0 | 228 | 0.2229 | 0.9809 | 0.9803 | 0.9802 | 0.9811 | 0.9803 | 0.0189 |
| 0.1837 | 7.0 | 266 | 0.1181 | 0.9871 | 0.9868 | 0.9868 | 0.9878 | 0.9868 | 0.0122 |
| 0.1131 | 8.0 | 304 | 0.0680 | 0.9937 | 0.9934 | 0.9934 | 0.9944 | 0.9934 | 0.0056 |
| 0.0526 | 9.0 | 342 | 0.0387 | 0.9937 | 0.9934 | 0.9934 | 0.9944 | 0.9934 | 0.0056 |
| 0.0283 | 10.0 | 380 | 0.0328 | 0.9873 | 0.9868 | 0.9869 | 0.9878 | 0.9868 | 0.0122 |
| 0.019 | 11.0 | 418 | 0.0224 | 0.9873 | 0.9868 | 0.9868 | 0.9889 | 0.9868 | 0.0111 |
| 0.0148 | 12.0 | 456 | 0.0201 | 0.9873 | 0.9868 | 0.9868 | 0.9889 | 0.9868 | 0.0111 |
| 0.0095 | 13.0 | 494 | 0.0396 | 0.9871 | 0.9868 | 0.9868 | 0.9878 | 0.9868 | 0.0122 |
| 0.007 | 14.0 | 532 | 0.0048 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 |
| 0.011 | 15.0 | 570 | 0.0036 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 |
| 0.0071 | 16.0 | 608 | 0.0092 | 0.9936 | 0.9934 | 0.9934 | 0.9941 | 0.9934 | 0.0059 |
| 0.0103 | 17.0 | 646 | 0.0148 | 0.9936 | 0.9934 | 0.9934 | 0.9944 | 0.9934 | 0.0056 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.3.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1