---
base_model: facebook/wav2vec2-xls-r-300m
datasets:
- common_voice_11_0
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-large-xls-r-300m-Hindi
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: common_voice_11_0
      type: common_voice_11_0
      config: hi
      split: test
      args: hi
    metrics:
    - type: wer
      value: 0.5158313579410768
      name: Wer
---

<!-- 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-Hindi

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_11_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7786
- Wer: 0.5158

## 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 6.0146        | 0.7214 | 400  | 2.8409          | 0.9970 |
| 1.2129        | 1.4427 | 800  | 1.1656          | 0.7795 |
| 0.7592        | 2.1641 | 1200 | 1.0091          | 0.7199 |
| 0.5798        | 2.8855 | 1600 | 0.9187          | 0.6614 |
| 0.4609        | 3.6069 | 2000 | 0.8386          | 0.6084 |
| 0.3828        | 4.3282 | 2400 | 0.8442          | 0.6097 |
| 0.3242        | 5.0496 | 2800 | 0.7907          | 0.5744 |
| 0.2619        | 5.7710 | 3200 | 0.7661          | 0.5485 |
| 0.2132        | 6.4923 | 3600 | 0.7943          | 0.5388 |
| 0.1911        | 7.2137 | 4000 | 0.7835          | 0.5278 |
| 0.1637        | 7.9351 | 4400 | 0.7786          | 0.5158 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1