---
language:
- ta
license: apache-2.0
widgets:
  - label: "Example 1"
    audio: "https://yourdomain.com/path/to/example1.wav"
  - label: "Example 2"
    audio: "https://yourdomain.com/path/to/example2.wav"
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
base_model: openai/whisper-small
model-index:
- name: carl-whisper-small-finetuned-tamil
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: Common Voice 13
      type: mozilla-foundation/common_voice_13_0
      config: ta
      split: None
      args: ta
    metrics:
    - type: wer
      value: 21.830330026321118
      name: Wer
---

<!-- 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. -->

# carl-whisper-small-finetuned-tamil

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 13 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4660
- Wer Ortho: 62.9625
- Wer: 21.8303

## 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: 10
- training_steps: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 0.3504        | 0.37  | 100  | 0.4660          | 62.9625   | 21.8303 |


### Framework versions

- Transformers 4.38.2
- Pytorch 1.11.0+cu102
- Datasets 2.18.0
- Tokenizers 0.15.2