pytorch wav2vec2 automatic-speech-recognition dataset:common_voice transformers generated_from_trainer license:apache-2.0 model-index
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2_common_voice_accents_us
  results: []
---

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# wav2vec2_common_voice_accents_us

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2722

## 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: 0.0003
- train_batch_size: 48
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 384
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 4.549         | 1.28  | 400  | 0.8521          |
| 0.4066        | 2.56  | 800  | 0.2407          |
| 0.2262        | 3.83  | 1200 | 0.2070          |
| 0.1828        | 5.11  | 1600 | 0.2134          |
| 0.1565        | 6.39  | 2000 | 0.2060          |
| 0.1448        | 7.67  | 2400 | 0.2100          |
| 0.1333        | 8.95  | 2800 | 0.2036          |
| 0.121         | 10.22 | 3200 | 0.2192          |
| 0.1146        | 11.5  | 3600 | 0.2154          |
| 0.1108        | 12.78 | 4000 | 0.2223          |
| 0.1017        | 14.06 | 4400 | 0.2331          |
| 0.094         | 15.34 | 4800 | 0.2257          |
| 0.0896        | 16.61 | 5200 | 0.2229          |
| 0.0825        | 17.89 | 5600 | 0.2229          |
| 0.0777        | 19.17 | 6000 | 0.2417          |
| 0.0719        | 20.45 | 6400 | 0.2433          |
| 0.0659        | 21.73 | 6800 | 0.2447          |
| 0.0651        | 23.0  | 7200 | 0.2446          |
| 0.0587        | 24.28 | 7600 | 0.2542          |
| 0.056         | 25.56 | 8000 | 0.2587          |
| 0.0521        | 26.84 | 8400 | 0.2640          |
| 0.0494        | 28.12 | 8800 | 0.2753          |
| 0.0465        | 29.39 | 9200 | 0.2722          |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.4
- Tokenizers 0.11.6
