Fraunhofer_Classical_multiclass_1
This model is a fine-tuned version of LaLegumbreArtificial/Fraunhofer_Classical on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0275
- Accuracy: 0.9908
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 |
|---|---|---|---|---|
| 0.0756 | 1.0 | 146 | 0.1135 | 0.9647 |
| 0.0435 | 2.0 | 292 | 0.0648 | 0.9785 |
| 0.0536 | 3.0 | 438 | 0.0442 | 0.984 |
| 0.0389 | 4.0 | 584 | 0.0285 | 0.9898 |
| 0.0292 | 5.0 | 730 | 0.0275 | 0.9908 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1