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_4
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# wav2vec2_common_voice_accents_4

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: 0.0047

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 4.615         | 1.28  | 400  | 0.8202          |
| 0.3778        | 2.56  | 800  | 0.1587          |
| 0.2229        | 3.85  | 1200 | 0.1027          |
| 0.1799        | 5.13  | 1600 | 0.0879          |
| 0.1617        | 6.41  | 2000 | 0.0772          |
| 0.1474        | 7.69  | 2400 | 0.0625          |
| 0.134         | 8.97  | 2800 | 0.0498          |
| 0.1213        | 10.26 | 3200 | 0.0429          |
| 0.1186        | 11.54 | 3600 | 0.0434          |
| 0.1118        | 12.82 | 4000 | 0.0312          |
| 0.1026        | 14.1  | 4400 | 0.0365          |
| 0.0951        | 15.38 | 4800 | 0.0321          |
| 0.0902        | 16.67 | 5200 | 0.0262          |
| 0.0843        | 17.95 | 5600 | 0.0208          |
| 0.0744        | 19.23 | 6000 | 0.0140          |
| 0.0718        | 20.51 | 6400 | 0.0204          |
| 0.0694        | 21.79 | 6800 | 0.0133          |
| 0.0636        | 23.08 | 7200 | 0.0104          |
| 0.0609        | 24.36 | 7600 | 0.0084          |
| 0.0559        | 25.64 | 8000 | 0.0050          |
| 0.0527        | 26.92 | 8400 | 0.0089          |
| 0.0495        | 28.21 | 8800 | 0.0058          |
| 0.0471        | 29.49 | 9200 | 0.0047          |


### Framework versions

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