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

Accuracy: 0.708
F1: 0.5491
Loss: 1.0891

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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Accuracy	F1	Validation Loss
1.927	1.0	250	0.372	0.1179	2.1230
1.3331	2.0	500	0.568	0.2523	1.4067
1.3706	3.0	750	0.648	0.3386	1.1545
1.0341	4.0	1000	0.656	0.3842	1.1280
1.1953	5.0	1250	0.7	0.4663	1.0257
0.4731	6.0	1500	0.686	0.4635	1.0457
0.4189	7.0	1750	0.672	0.4710	1.0784
0.5092	8.0	2000	0.688	0.5073	1.0660
0.4302	9.0	2250	0.708	0.5301	1.0772
0.496	10.0	2500	0.708	0.5491	1.0891

Framework versions

Transformers 4.48.3
Pytorch 2.5.1+cu124
Datasets 3.5.0
Tokenizers 0.21.0

codymd/distilhubert-finetuned-linnut-sm

distilhubert-finetuned-linnut-sm

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

codymd/
distilhubert-finetuned-linnut-sm