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beit_large512_fine_tuned
This model is a fine-tuned version of microsoft/beit-base-patch16-384 on the beans dataset. It achieves the following results on the evaluation set:
- Loss: 0.0353
- Accuracy: 0.9925
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 4.6571 | 0.98 | 16 | 0.3870 | 0.8722 |
| 0.2299 | 1.97 | 32 | 0.0632 | 0.9850 |
| 0.1435 | 2.95 | 48 | 0.0353 | 0.9925 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cpu
- Datasets 2.13.1
- Tokenizers 0.13.3
