---
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: 1.3902
- Wer: 0.7443

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 6.9225        | 2.3   | 200  | 3.3972          | 1.0    |
| 1.4526        | 4.59  | 400  | 1.0196          | 0.7959 |
| 0.5384        | 6.89  | 600  | 1.0260          | 0.7790 |
| 0.3483        | 9.19  | 800  | 1.0932          | 0.7740 |
| 0.2428        | 11.49 | 1000 | 1.2085          | 0.7747 |
| 0.1839        | 13.79 | 1200 | 1.2716          | 0.7750 |
| 0.147         | 16.09 | 1400 | 1.2895          | 0.7665 |
| 0.1238        | 18.39 | 1600 | 1.2995          | 0.7585 |
| 0.1046        | 20.69 | 1800 | 1.3891          | 0.7550 |
| 0.0946        | 22.98 | 2000 | 1.3820          | 0.7603 |
| 0.0856        | 25.29 | 2200 | 1.3909          | 0.7438 |
| 0.0753        | 27.58 | 2400 | 1.3841          | 0.7431 |
| 0.075         | 29.88 | 2600 | 1.3902          | 0.7443 |


### Framework versions

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