---
language:
- ta
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- tamilcustomvoice
metrics:
- wer
model-index:
- name: Whisper tiny custom
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: custom dataset
      type: tamilcustomvoice
    metrics:
    - name: Wer
      type: wer
      value: 7.28476821192053
---

<!-- 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 tiny custom

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the custom dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0315
- Wer Ortho: 9.2105
- Wer: 7.2848

## 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: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 1.6536        | 2.5   | 50   | 0.4681          | 57.8947   | 50.9934 |
| 0.0732        | 5.0   | 100  | 0.0820          | 19.7368   | 15.2318 |
| 0.0076        | 7.5   | 150  | 0.0396          | 9.2105    | 7.9470  |
| 0.0013        | 10.0  | 200  | 0.0336          | 9.2105    | 8.6093  |
| 0.0007        | 12.5  | 250  | 0.0356          | 7.8947    | 5.9603  |
| 0.0005        | 15.0  | 300  | 0.0339          | 7.8947    | 5.9603  |
| 0.0004        | 17.5  | 350  | 0.0326          | 7.8947    | 5.9603  |
| 0.0003        | 20.0  | 400  | 0.0323          | 7.8947    | 5.9603  |
| 0.0003        | 22.5  | 450  | 0.0320          | 9.2105    | 7.2848  |
| 0.0002        | 25.0  | 500  | 0.0315          | 9.2105    | 7.2848  |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1