Train-Test-Augmentation-V4-beit-base
This model is a fine-tuned version of microsoft/beit-base-patch16-224-pt22k-ft22k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4701
- Accuracy: 0.8557
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: 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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6584 | 1.0 | 55 | 0.6744 | 0.7946 |
| 0.2762 | 2.0 | 110 | 0.5429 | 0.8234 |
| 0.1144 | 3.0 | 165 | 0.5259 | 0.8336 |
| 0.0487 | 4.0 | 220 | 0.5111 | 0.8404 |
| 0.0218 | 5.0 | 275 | 0.4701 | 0.8557 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.15.2
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Model tree for ahmedesmail16/Train-Test-Augmentation-V4-beit-base
Base model
microsoft/beit-base-patch16-224-pt22k-ft22k