---
license: apache-2.0
base_model: LaLegumbreArtificial/Fraunhofer_Classical
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Fraunhofer_Classical_multiclass
  results: []
---

<!-- 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 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