distilhubert-finetuned-birdclef

This model is a fine-tuned version of ntu-spml/distilhubert on the Birdclef 2024 dataset. It achieves the following results on the evaluation set:

• Loss: 1.8592
• Accuracy: 0.6975
• F1 Macro: 0.4507
• F1 Weighted: 0.6871

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 10
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1 Macro	F1 Weighted
3.3212	1.0	2446	3.4889	0.2343	0.0453	0.1567
2.5841	2.0	4892	2.1989	0.5123	0.1673	0.4489
1.5152	3.0	7338	1.8349	0.5871	0.2449	0.5452
1.4771	4.0	9784	1.6815	0.6300	0.3213	0.6048
1.0287	5.0	12230	1.6218	0.6627	0.3498	0.6462
0.9425	6.0	14676	1.6177	0.6688	0.3835	0.6511
0.291	7.0	17122	1.7205	0.6832	0.3903	0.6682
0.244	8.0	19568	1.7817	0.6811	0.4049	0.6706
0.0593	9.0	22014	1.8653	0.6881	0.4282	0.6755
0.0754	10.0	24460	1.8877	0.6917	0.4320	0.6823

Framework versions

• Transformers 4.38.2
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2