Fraunhofer_Classical_multiclass
This model is a fine-tuned version of LaLegumbreArtificial/Fraunhofer_Classical on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0439
- Accuracy: 0.9871
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 |
---|---|---|---|---|
0.138 | 1.0 | 80 | 0.0890 | 0.9667 |
0.0982 | 2.0 | 160 | 0.0823 | 0.9695 |
0.0686 | 3.0 | 240 | 0.0607 | 0.9757 |
0.0536 | 4.0 | 320 | 0.0550 | 0.9808 |
0.0646 | 5.0 | 400 | 0.0439 | 0.9871 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for LaLegumbreArtificial/Fraunhofer_Classical_multiclass
Base model
microsoft/beit-base-patch16-224-pt22k-ft22k