asl_aplhabet_img_classifier_v3
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.7922
- Accuracy: 0.7549
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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 272 | 3.0038 | 0.3802 |
| 3.0097 | 2.0 | 544 | 2.5739 | 0.5880 |
| 3.0097 | 3.0 | 816 | 2.2886 | 0.6464 |
| 2.3653 | 4.0 | 1088 | 2.0810 | 0.7099 |
| 2.3653 | 5.0 | 1360 | 1.9355 | 0.7407 |
| 1.9884 | 6.0 | 1632 | 1.8371 | 0.7582 |
| 1.9884 | 7.0 | 1904 | 1.7752 | 0.7701 |
| 1.8003 | 8.0 | 2176 | 1.7531 | 0.7674 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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