0.50-500Train-100Test-beit-base

This model is a fine-tuned version of microsoft/beit-base-patch16-224-pt22k-ft22k on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.7300
• Accuracy: 0.8262

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: 16
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 7

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.4603	0.9973	92	0.6572	0.7782
0.223	1.9946	184	0.6184	0.7956
0.0749	2.9919	276	0.6076	0.8262
0.0218	4.0	369	0.7377	0.8140
0.0082	4.9973	461	0.7851	0.8061
0.0023	5.9946	553	0.7284	0.8227
0.0037	6.9810	644	0.7300	0.8262

Framework versions

• Transformers 4.41.2
• Pytorch 2.1.2
• Datasets 2.19.2
• Tokenizers 0.19.1