metadata

license: apache-2.0
base_model: LaLegumbreArtificial/Fraunhofer_Classical
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: Fraunhofer_Classical_multiclass_1
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: imagefolder
          type: imagefolder
          config: default
          split: train
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.99075

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