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-v3
  results: []
---

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# ai-light-dance_singing2_ft_wav2vec2-large-xlsr-53-5gram-v3

This model is a fine-tuned version of [gary109/ai-light-dance_singing2_ft_wav2vec2-large-xlsr-53-v2](https://huggingface.co/gary109/ai-light-dance_singing2_ft_wav2vec2-large-xlsr-53-v2) on the GARY109/AI_LIGHT_DANCE - ONSET-SINGING2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5265
- Wer: 0.2256

## 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-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.2546        | 1.0   | 280  | 0.6004          | 0.2796 |
| 0.2325        | 2.0   | 560  | 0.6337          | 0.2729 |
| 0.2185        | 3.0   | 840  | 0.5546          | 0.2299 |
| 0.1988        | 4.0   | 1120 | 0.5265          | 0.2256 |
| 0.1755        | 5.0   | 1400 | 0.5577          | 0.2212 |
| 0.1474        | 6.0   | 1680 | 0.6353          | 0.2241 |
| 0.1498        | 7.0   | 1960 | 0.5758          | 0.2086 |
| 0.1252        | 8.0   | 2240 | 0.5738          | 0.2052 |
| 0.1174        | 9.0   | 2520 | 0.5994          | 0.2048 |
| 0.1035        | 10.0  | 2800 | 0.5988          | 0.2038 |


### Framework versions

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