---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-telugu-asr
  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-telugu-asr

This model is a fine-tuned version of [henilp105/wav2vec2-large-xls-r-300m-telugu-asr](https://huggingface.co/henilp105/wav2vec2-large-xls-r-300m-telugu-asr) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1050
- Wer: 0.6656

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 6.0506        | 2.3   | 200  | 0.8841          | 0.7564 |
| 0.6354        | 4.59  | 400  | 0.7448          | 0.6912 |
| 0.3934        | 6.89  | 600  | 0.8321          | 0.6929 |
| 0.2652        | 9.19  | 800  | 0.9529          | 0.6984 |
| 0.2022        | 11.49 | 1000 | 0.9490          | 0.6979 |
| 0.1514        | 13.79 | 1200 | 1.0025          | 0.6869 |
| 0.124         | 16.09 | 1400 | 1.0367          | 0.6799 |
| 0.1007        | 18.39 | 1600 | 1.0658          | 0.6734 |
| 0.0875        | 20.69 | 1800 | 1.0758          | 0.6779 |
| 0.0838        | 22.98 | 2000 | 1.0999          | 0.6701 |
| 0.0745        | 25.29 | 2200 | 1.1020          | 0.6708 |
| 0.0641        | 27.58 | 2400 | 1.1140          | 0.6683 |
| 0.0607        | 29.88 | 2600 | 1.1050          | 0.6656 |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.10.0+cu113
- Datasets 1.18.3
- Tokenizers 0.13.2