Birdsclassification

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.3057
• Accuracy: 0.9307

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: 0.0003
• train_batch_size: 64
• eval_batch_size: 64
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 256
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 16
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
5.42	1.0	262	3.6698	0.7571
1.7968	2.0	525	0.9179	0.8396
0.6598	3.0	787	0.6370	0.8654
0.4867	4.0	1050	0.5493	0.8765
0.4055	5.0	1312	0.5093	0.8833
0.3513	6.0	1575	0.4602	0.8892
0.3053	7.0	1837	0.4350	0.8977
0.2692	8.0	2100	0.4130	0.9021
0.2446	9.0	2362	0.4218	0.9018
0.2267	10.0	2625	0.3667	0.9130
0.2018	11.0	2887	0.3632	0.9154
0.1842	12.0	3150	0.3533	0.9154
0.1636	13.0	3412	0.3396	0.9206
0.1511	14.0	3675	0.3125	0.9266
0.1411	15.0	3937	0.2833	0.9329
0.1259	15.97	4192	0.3057	0.9307

Framework versions

• Transformers 4.38.2
• Pytorch 2.1.2
• Datasets 2.18.0
• Tokenizers 0.15.2