| --- |
| license: apache-2.0 |
| base_model: LaLegumbreArtificial/Fraunhofer_Classical |
| tags: |
| - generated_from_trainer |
| datasets: |
| - imagefolder |
| metrics: |
| - accuracy |
| model-index: |
| - name: Fraunhofer_Classical_multiclass |
| results: |
| - task: |
| name: Image Classification |
| type: image-classification |
| dataset: |
| name: imagefolder |
| type: imagefolder |
| config: default |
| split: test |
| args: default |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.761384335154827 |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # Fraunhofer_Classical_multiclass |
|
|
| This model is a fine-tuned version of [LaLegumbreArtificial/Fraunhofer_Classical](https://huggingface.co/LaLegumbreArtificial/Fraunhofer_Classical) on the imagefolder dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.1740 |
| - Accuracy: 0.7614 |
|
|
| ## 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 | |
| |:-------------:|:------:|:----:|:---------------:|:--------:| |
| | 0.0716 | 0.9976 | 208 | 0.8637 | 0.7752 | |
| | 0.0478 | 2.0 | 417 | 0.7157 | 0.8339 | |
| | 0.0408 | 2.9976 | 625 | 0.9172 | 0.8080 | |
| | 0.031 | 4.0 | 834 | 0.9607 | 0.8104 | |
| | 0.0258 | 4.9880 | 1040 | 1.1740 | 0.7614 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.44.0 |
| - Pytorch 2.4.0 |
| - Datasets 2.21.0 |
| - Tokenizers 0.19.1 |
|
|
