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_singing2_ft_wav2vec2-large-xlsr-53-5gram-v4-2
  results: []
---

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# ai-light-dance_singing2_ft_wav2vec2-large-xlsr-53-5gram-v4-2

This model is a fine-tuned version of [gary109/ai-light-dance_singing2_ft_wav2vec2-large-xlsr-53-5gram-v4-1](https://huggingface.co/gary109/ai-light-dance_singing2_ft_wav2vec2-large-xlsr-53-5gram-v4-1) on the GARY109/AI_LIGHT_DANCE - ONSET-SINGING2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2691
- Wer: 0.0910

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 10.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.2664        | 1.0   | 8969  | 0.3347          | 0.1645 |
| 0.2032        | 2.0   | 17938 | 0.3170          | 0.1662 |
| 0.1888        | 3.0   | 26907 | 0.3188          | 0.1317 |
| 0.1774        | 4.0   | 35876 | 0.2885          | 0.1195 |
| 0.0696        | 5.0   | 44845 | 0.2703          | 0.1105 |
| 0.254         | 6.0   | 53814 | 0.2817          | 0.0972 |
| 0.0464        | 7.0   | 62783 | 0.2691          | 0.0910 |
| 0.0426        | 8.0   | 71752 | 0.3033          | 0.0875 |
| 0.035         | 9.0   | 80721 | 0.3150          | 0.0841 |
| 0.0274        | 10.0  | 89690 | 0.3073          | 0.0816 |


### Framework versions

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