---
library_name: transformers
language:
- ta
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- sp03/tamil
metrics:
- wer
model-index:
- name: Whisper Small ta - Sp03
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: sp03/tamil
      config: default
      split: None
      args: 'config: ta, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 100.0
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Small ta - Sp03

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 3.6056
- Wer: 100.0

## 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: 0.001
- train_batch_size: 4
- eval_batch_size: 1
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer   |
|:-------------:|:-----:|:----:|:---------------:|:-----:|
| 1.4066        | 1.0   | 4    | 9.3832          | 100.0 |
| 21.3162       | 2.0   | 8    | 21.2056         | 100.0 |
| 11.2822       | 3.0   | 12   | 7.6851          | 100.0 |
| 6.0345        | 4.0   | 16   | 4.8468          | 100.0 |
| 3.8909        | 5.0   | 20   | 3.6056          | 100.0 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0