---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-hi-wx1
  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-large-xls-r-300m-hi-wx1

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: 0.6966
- Wer: 0.3424

## 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: 0.00024
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1500
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 11.0193       | 1.36  | 200  | 5.6992          | 1.0    |
| 3.9285        | 2.72  | 400  | 3.4430          | 1.0    |
| 3.293         | 4.08  | 600  | 2.7707          | 1.0    |
| 1.2714        | 5.44  | 800  | 0.8479          | 0.6015 |
| 0.6469        | 6.8   | 1000 | 0.7087          | 0.5412 |
| 0.4982        | 8.16  | 1200 | 0.6655          | 0.5116 |
| 0.4131        | 9.52  | 1400 | 0.6422          | 0.4845 |
| 0.3653        | 10.88 | 1600 | 0.6452          | 0.4700 |
| 0.3177        | 12.24 | 1800 | 0.7519          | 0.5236 |
| 0.2771        | 13.6  | 2000 | 0.6238          | 0.4444 |
| 0.2424        | 14.96 | 2200 | 0.6317          | 0.4458 |
| 0.2207        | 16.33 | 2400 | 0.6634          | 0.4144 |
| 0.1997        | 17.68 | 2600 | 0.6469          | 0.4110 |
| 0.1843        | 19.05 | 2800 | 0.6958          | 0.4162 |
| 0.1705        | 20.41 | 3000 | 0.6658          | 0.3992 |
| 0.1535        | 21.77 | 3200 | 0.6829          | 0.4136 |
| 0.1492        | 23.13 | 3400 | 0.6628          | 0.4018 |
| 0.1383        | 24.49 | 3600 | 0.6603          | 0.4020 |
| 0.1334        | 25.85 | 3800 | 0.7079          | 0.3914 |
| 0.1215        | 27.21 | 4000 | 0.7016          | 0.3904 |
| 0.1211        | 28.57 | 4200 | 0.7232          | 0.3963 |
| 0.1125        | 29.93 | 4400 | 0.7258          | 0.3879 |
| 0.1074        | 31.29 | 4600 | 0.7476          | 0.3900 |
| 0.0965        | 32.65 | 4800 | 0.7120          | 0.3734 |
| 0.0916        | 34.01 | 5000 | 0.6694          | 0.3730 |
| 0.0865        | 35.37 | 5200 | 0.7181          | 0.3680 |
| 0.0822        | 36.73 | 5400 | 0.6698          | 0.3554 |
| 0.0757        | 38.09 | 5600 | 0.7035          | 0.3627 |
| 0.0723        | 39.45 | 5800 | 0.6832          | 0.3575 |
| 0.0746        | 40.81 | 6000 | 0.6942          | 0.3508 |
| 0.0667        | 42.18 | 6200 | 0.7075          | 0.3523 |
| 0.0638        | 43.54 | 6400 | 0.7009          | 0.3473 |
| 0.0585        | 44.89 | 6600 | 0.6887          | 0.3443 |
| 0.0562        | 46.26 | 6800 | 0.6888          | 0.3454 |
| 0.0534        | 47.62 | 7000 | 0.7048          | 0.3438 |
| 0.0481        | 48.98 | 7200 | 0.6966          | 0.3424 |


### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0