---
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
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# 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   |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1