---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-hindi
  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-xlsr-hindi

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0220
- Wer: 0.5697

## 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: 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: 500
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.6122        | 1.81  | 400  | 3.3749          | 1.0    |
| 1.6592        | 3.61  | 800  | 1.0003          | 0.7554 |
| 0.7745        | 5.42  | 1200 | 0.9482          | 0.6972 |
| 0.6286        | 7.22  | 1600 | 1.0754          | 0.6750 |
| 0.5413        | 9.03  | 2000 | 0.9040          | 0.6405 |
| 0.4833        | 10.84 | 2400 | 0.9086          | 0.6116 |
| 0.4331        | 12.64 | 2800 | 0.9273          | 0.6283 |
| 0.4047        | 14.45 | 3200 | 1.0076          | 0.6138 |
| 0.3739        | 16.25 | 3600 | 0.9818          | 0.6018 |
| 0.3445        | 18.06 | 4000 | 0.9948          | 0.5952 |
| 0.3305        | 19.86 | 4400 | 0.9897          | 0.5834 |
| 0.3107        | 21.67 | 4800 | 1.0022          | 0.5751 |
| 0.2879        | 23.48 | 5200 | 1.0235          | 0.5744 |
| 0.2836        | 25.28 | 5600 | 1.0238          | 0.5765 |
| 0.2706        | 27.09 | 6000 | 1.0276          | 0.5694 |
| 0.2656        | 28.89 | 6400 | 1.0220          | 0.5697 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0