---
library_name: transformers
language:
- ta
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper tiny ta - Sanchit Gandhi
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: ta
      split: None
      args: 'config: ta, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 81.81818181818183
---

<!-- 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 ta - Sanchit Gandhi

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1323
- Wer: 81.8182
- Cer: 25.8981

## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- 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
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     | Cer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|:-------:|
| 0.3684        | 1.5873  | 100  | 0.7662          | 96.3317 | 49.9906 |
| 0.1868        | 3.1746  | 200  | 0.8380          | 86.7624 | 29.6596 |
| 0.097         | 4.7619  | 300  | 0.9112          | 85.0080 | 29.5091 |
| 0.0481        | 6.3492  | 400  | 0.9833          | 85.4864 | 29.9041 |
| 0.0332        | 7.9365  | 500  | 0.9751          | 83.0941 | 30.1862 |
| 0.0154        | 9.5238  | 600  | 1.0561          | 85.4864 | 29.2082 |
| 0.0064        | 11.1111 | 700  | 1.1354          | 83.5726 | 27.3462 |
| 0.003         | 12.6984 | 800  | 1.1157          | 83.7321 | 27.1958 |
| 0.0006        | 14.2857 | 900  | 1.1344          | 82.7751 | 26.4435 |
| 0.0004        | 15.8730 | 1000 | 1.1323          | 81.8182 | 25.8981 |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0