---
base_model: facebook/wav2vec2-large-xlsr-53
datasets:
- fleurs
library_name: transformers
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-large-xlsr-53-Hindi-Version1
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: fleurs
      type: fleurs
      config: hi_in
      split: None
      args: hi_in
    metrics:
    - type: wer
      value: 0.5457385531582544
      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-xlsr-53-Hindi-Version1

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7287
- Wer: 0.5457

## 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: 3e-05
- 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: 70
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 3.6017        | 6.7568  | 500  | 3.5280          | 1.0    |
| 3.3879        | 13.5135 | 1000 | 3.3755          | 1.0    |
| 3.3566        | 20.2703 | 1500 | 3.3544          | 1.0    |
| 3.3133        | 27.0270 | 2000 | 3.2753          | 1.0    |
| 2.216         | 33.7838 | 2500 | 1.8757          | 0.9159 |
| 1.2972        | 40.5405 | 3000 | 1.0386          | 0.6969 |
| 1.0939        | 47.2973 | 3500 | 0.8590          | 0.6190 |
| 1.0188        | 54.0541 | 4000 | 0.7791          | 0.5797 |
| 0.9468        | 60.8108 | 4500 | 0.7461          | 0.5575 |
| 0.9806        | 67.5676 | 5000 | 0.7287          | 0.5457 |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1