đ ai-light-dance_singing2_ft_wav2vec2-large-xlsr-53
This model is a fine - tuned version of facebook/wav2vec2-large-xlsr-53 on the /WORKSPACE/ASANTE/AI-LIGHT-DANCE_DATASETS/AI_LIGHT_DANCE.PY - ONSET-SINGING2 dataset. It offers a solution for automatic speech recognition tasks, achieving specific evaluation results to enhance the accuracy of speech recognition.
đ Quick Start
This model is a fine - tuned version of facebook/wav2vec2-large-xlsr-53 on the /WORKSPACE/ASANTE/AI-LIGHT-DANCE_DATASETS/AI_LIGHT_DANCE.PY - ONSET-SINGING2 dataset.
It achieves the following results on the evaluation set:
đ Documentation
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: 4e - 06
- train_batch_size: 10
- eval_batch_size: 10
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 160
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e - 08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 30.0
- mixed_precision_training: Native AMP
Training results
| Training Loss |
Epoch |
Step |
Validation Loss |
Wer |
| 27.4755 |
1.0 |
112 |
23.2618 |
1.0 |
| 5.5145 |
2.0 |
224 |
5.2213 |
1.0 |
| 4.2211 |
3.0 |
336 |
4.1673 |
1.0 |
| 3.8386 |
4.0 |
448 |
3.8253 |
1.0 |
| 3.5531 |
5.0 |
560 |
3.6286 |
1.0 |
| 3.5215 |
6.0 |
672 |
3.4762 |
0.9864 |
| 3.3493 |
7.0 |
784 |
3.3549 |
0.9847 |
| 3.1264 |
8.0 |
896 |
3.1797 |
0.9759 |
| 2.7557 |
9.0 |
1008 |
2.8703 |
0.9865 |
| 2.6345 |
10.0 |
1120 |
2.6736 |
0.9970 |
| 2.4297 |
11.0 |
1232 |
2.5638 |
1.0337 |
| 2.3057 |
12.0 |
1344 |
2.3680 |
0.9839 |
| 2.1436 |
13.0 |
1456 |
2.2367 |
0.9648 |
| 2.0856 |
14.0 |
1568 |
2.1635 |
0.9586 |
| 2.0035 |
15.0 |
1680 |
2.0945 |
0.9645 |
| 1.9134 |
16.0 |
1792 |
2.0395 |
0.9630 |
| 1.9443 |
17.0 |
1904 |
2.0017 |
0.9401 |
| 1.8988 |
18.0 |
2016 |
1.9514 |
0.9493 |
| 1.8141 |
19.0 |
2128 |
1.9111 |
0.9475 |
| 1.8344 |
20.0 |
2240 |
1.8790 |
0.9395 |
| 1.7775 |
21.0 |
2352 |
1.8616 |
0.9503 |
| 1.7517 |
22.0 |
2464 |
1.8333 |
0.9433 |
| 1.7037 |
23.0 |
2576 |
1.8156 |
0.9372 |
| 1.7158 |
24.0 |
2688 |
1.7961 |
0.9482 |
| 1.7111 |
25.0 |
2800 |
1.7817 |
0.9422 |
| 1.69 |
26.0 |
2912 |
1.7819 |
0.9430 |
| 1.6889 |
27.0 |
3024 |
1.7721 |
0.9386 |
| 1.6546 |
28.0 |
3136 |
1.7647 |
0.9453 |
| 1.6542 |
29.0 |
3248 |
1.7653 |
0.9375 |
| 1.647 |
30.0 |
3360 |
1.7583 |
0.9386 |
Framework versions
- Transformers 4.21.0.dev0
- Pytorch 1.9.1+cu102
- Datasets 2.3.3.dev0
- Tokenizers 0.12.1
đ License
This model is licensed under the Apache - 2.0 license.
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