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-g4-firstseconds
results: []
wav2vec2-base-music_genre_classifier-g4-firstseconds
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: 1.4970
- Accuracy: 0.8304
- F1: 0.8244
- Recall: 0.8262
- Precision: 0.8260
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 |
|---|---|---|---|---|---|---|---|
| 1.1447 | 1.0 | 2393 | 1.2684 | 0.6524 | 0.6382 | 0.6533 | 0.6527 |
| 0.7302 | 2.0 | 4786 | 0.8886 | 0.7458 | 0.7421 | 0.7479 | 0.7637 |
| 0.521 | 3.0 | 7179 | 0.8755 | 0.7701 | 0.7686 | 0.7715 | 0.7934 |
| 0.3648 | 4.0 | 9572 | 1.0389 | 0.7731 | 0.7723 | 0.7673 | 0.7928 |
| 0.6132 | 5.0 | 11965 | 1.0694 | 0.7997 | 0.7955 | 0.7943 | 0.8170 |
| 0.6512 | 6.0 | 14358 | 1.2190 | 0.7886 | 0.7864 | 0.7864 | 0.7984 |
| 0.0851 | 7.0 | 16751 | 1.2496 | 0.8022 | 0.7959 | 0.7973 | 0.8082 |
| 0.0881 | 8.0 | 19144 | 1.2582 | 0.8127 | 0.8088 | 0.8105 | 0.8098 |
| 0.1063 | 9.0 | 21537 | 1.4087 | 0.8148 | 0.8119 | 0.8121 | 0.8176 |
| 0.4205 | 10.0 | 23930 | 1.4825 | 0.8055 | 0.8001 | 0.8019 | 0.8158 |
| 0.0478 | 11.0 | 26323 | 1.4240 | 0.8109 | 0.8023 | 0.8031 | 0.8082 |
| 0.0037 | 12.0 | 28716 | 1.3865 | 0.8248 | 0.8182 | 0.8199 | 0.8202 |
| 0.0236 | 13.0 | 31109 | 1.4570 | 0.8279 | 0.8230 | 0.8232 | 0.8250 |
| 0.0094 | 14.0 | 33502 | 1.4892 | 0.8289 | 0.8227 | 0.8248 | 0.8249 |
| 0.0002 | 15.0 | 35895 | 1.4970 | 0.8304 | 0.8244 | 0.8262 | 0.8260 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3