metadata

library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - recall
  - precision
model-index:
  - name: wav2vec2-base-music_genre_classifier-g3b
    results: []

wav2vec2-base-music_genre_classifier-g3b

This model is a fine-tuned version of facebook/wav2vec2-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.3709
Accuracy: 0.7380
F1: 0.7356
Recall: 0.7395
Precision: 0.7400

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: 3e-05
train_batch_size: 12
eval_batch_size: 12
seed: 42
optimizer: Use 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: 15
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Recall	Precision
2.3444	1.0	276	2.2888	0.3618	0.2663	0.3495	0.2702
1.946	2.0	552	1.7679	0.4880	0.4277	0.4778	0.5072
1.6394	3.0	828	1.4655	0.5565	0.4966	0.5463	0.5089
1.2346	4.0	1104	1.3279	0.5974	0.5654	0.5937	0.6372
0.8945	5.0	1380	1.2718	0.6226	0.6021	0.6178	0.6240
0.7872	6.0	1656	1.1310	0.6671	0.6594	0.6691	0.6826
0.5562	7.0	1932	1.1743	0.6743	0.6677	0.6730	0.6857
0.65	8.0	2208	1.0722	0.7163	0.7178	0.7179	0.7394
0.3239	9.0	2484	1.1846	0.6899	0.6863	0.6909	0.6997
0.3885	10.0	2760	1.2243	0.7031	0.6994	0.7072	0.7126
0.1529	11.0	3036	1.2539	0.7175	0.7193	0.7195	0.7245
0.4527	12.0	3312	1.3231	0.7188	0.7116	0.7182	0.7220
0.324	13.0	3588	1.3190	0.7344	0.7360	0.7368	0.7409
0.0277	14.0	3864	1.3623	0.7356	0.7340	0.7370	0.7407
0.0276	15.0	4140	1.3709	0.7380	0.7356	0.7395	0.7400

Framework versions

Transformers 4.46.2
Pytorch 2.5.0+cu121
Datasets 3.1.0
Tokenizers 0.20.3