---
language:
- te
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- Chai_Bisket_Stories_16-08-2021_14-17
metrics:
- wer
model-index:
- name: Whisper Small Telugu - Naga Budigam
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Chai_Bisket_Stories_16-08-2021_14-17
      type: Chai_Bisket_Stories_16-08-2021_14-17
      config: None
      split: None
      args: 'config: te, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 77.48711850971065
---

<!-- 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. -->

# Whisper Small Telugu - Naga Budigam

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Chai_Bisket_Stories_16-08-2021_14-17 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7063
- Wer: 77.4871

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2933        | 2.62  | 500  | 0.3849          | 86.6429 |
| 0.0692        | 5.24  | 1000 | 0.3943          | 82.7190 |
| 0.0251        | 7.85  | 1500 | 0.4720          | 82.4415 |
| 0.0098        | 10.47 | 2000 | 0.5359          | 81.6092 |
| 0.0061        | 13.09 | 2500 | 0.5868          | 75.9413 |
| 0.0025        | 15.71 | 3000 | 0.6235          | 76.6944 |
| 0.0009        | 18.32 | 3500 | 0.6634          | 78.3987 |
| 0.0005        | 20.94 | 4000 | 0.6776          | 77.1700 |
| 0.0002        | 23.56 | 4500 | 0.6995          | 78.2798 |
| 0.0001        | 26.18 | 5000 | 0.7063          | 77.4871 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0
- Datasets 2.7.1
- Tokenizers 0.13.2