README.md

---
library_name: transformers
language:
- te
base_model: openai/whisper-small-v3
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Small Te - Prashanth Kattoju
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 17
      type: mozilla-foundation/common_voice_17_0
      config: te
      split: test
      args: te
    metrics:
    - name: Wer
      type: wer
      value: 15.384615384615385
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Small Te - Prashanth Kattoju

This model is a fine-tuned version of [openai/whisper-small-v3](https://huggingface.co/openai/whisper-small-v3) on the Common Voice 17 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0903
- Wer Ortho: 40.6593
- Wer: 15.3846

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| 0.0106        | 8.6207 | 1000 | 0.0903          | 40.6593   | 15.3846 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1

### Future Scope
More training need to done with generalized data for more accurate results