---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2_common_voice_accents_indian
  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_indian

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: 0.2692

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 4.5186        | 1.28  | 400  | 0.6937          |
| 0.3485        | 2.56  | 800  | 0.2323          |
| 0.2229        | 3.83  | 1200 | 0.2195          |
| 0.1877        | 5.11  | 1600 | 0.2147          |
| 0.1618        | 6.39  | 2000 | 0.2058          |
| 0.1434        | 7.67  | 2400 | 0.2077          |
| 0.132         | 8.95  | 2800 | 0.1995          |
| 0.1223        | 10.22 | 3200 | 0.2146          |
| 0.1153        | 11.5  | 3600 | 0.2117          |
| 0.1061        | 12.78 | 4000 | 0.2071          |
| 0.1003        | 14.06 | 4400 | 0.2219          |
| 0.0949        | 15.34 | 4800 | 0.2204          |
| 0.0889        | 16.61 | 5200 | 0.2162          |
| 0.0824        | 17.89 | 5600 | 0.2243          |
| 0.0784        | 19.17 | 6000 | 0.2323          |
| 0.0702        | 20.45 | 6400 | 0.2325          |
| 0.0665        | 21.73 | 6800 | 0.2334          |
| 0.0626        | 23.0  | 7200 | 0.2411          |
| 0.058         | 24.28 | 7600 | 0.2473          |
| 0.054         | 25.56 | 8000 | 0.2591          |
| 0.0506        | 26.84 | 8400 | 0.2577          |
| 0.0484        | 28.12 | 8800 | 0.2633          |
| 0.0453        | 29.39 | 9200 | 0.2692          |


### Framework versions

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