Fraunhofer_Classical_multiclass

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: 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