---
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: 4.0959
- Wer: 1.0406

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.6321        | 2.04  | 200  | 2.3063          | 0.9872 |
| 1.8629        | 4.08  | 400  | 2.4143          | 0.9926 |
| 1.3881        | 6.12  | 600  | 2.5862          | 0.9795 |
| 1.0565        | 8.16  | 800  | 2.6708          | 1.0191 |
| 0.7681        | 10.2  | 1000 | 3.1001          | 0.9992 |
| 0.5867        | 12.24 | 1200 | 3.4503          | 1.0228 |
| 0.4289        | 14.29 | 1400 | 3.5382          | 1.0165 |
| 0.3618        | 16.33 | 1600 | 3.5116          | 0.9835 |
| 0.3229        | 18.37 | 1800 | 3.6524          | 1.0093 |
| 0.2483        | 20.41 | 2000 | 3.6222          | 1.0319 |
| 0.2215        | 22.45 | 2200 | 3.9824          | 1.0414 |
| 0.1833        | 24.49 | 2400 | 3.9272          | 1.0393 |
| 0.1706        | 26.53 | 2600 | 3.9290          | 1.0425 |
| 0.1463        | 28.57 | 2800 | 4.0959          | 1.0406 |


### Framework versions

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