pytorch tensorboard wav2vec2 automatic-speech-recognition transformers gary109/AI_Light_Dance generated_from_trainer model-index
---
tags:
- automatic-speech-recognition
- gary109/AI_Light_Dance
- generated_from_trainer
model-index:
- name: ai-light-dance_singing_ft_wav2vec2-large-xlsr-53-5gram-v1
  results: []
---

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# ai-light-dance_singing_ft_wav2vec2-large-xlsr-53-5gram-v1

This model is a fine-tuned version of [gary109/ai-light-dance_singing_ft_wav2vec2-large-xlsr-53-5gram](https://huggingface.co/gary109/ai-light-dance_singing_ft_wav2vec2-large-xlsr-53-5gram) on the GARY109/AI_LIGHT_DANCE - ONSET-SINGING dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4123
- Wer: 0.1668

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 10.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.2696        | 1.0   | 552  | 0.4421          | 0.2013 |
| 0.2498        | 2.0   | 1104 | 0.4389          | 0.1887 |
| 0.2387        | 3.0   | 1656 | 0.4154          | 0.1788 |
| 0.1902        | 4.0   | 2208 | 0.4143          | 0.1753 |
| 0.1896        | 5.0   | 2760 | 0.4123          | 0.1668 |
| 0.1658        | 6.0   | 3312 | 0.4366          | 0.1651 |
| 0.1312        | 7.0   | 3864 | 0.4309          | 0.1594 |
| 0.1186        | 8.0   | 4416 | 0.4432          | 0.1561 |
| 0.1476        | 9.0   | 4968 | 0.4400          | 0.1569 |
| 0.1027        | 10.0  | 5520 | 0.4389          | 0.1554 |


### Framework versions

- Transformers 4.21.0.dev0
- Pytorch 1.9.1+cu102
- Datasets 2.3.3.dev0
- Tokenizers 0.12.1
