metadata
language:
- ta
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- fixie-ai/common_voice_17_0
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Tiny ta
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 17.0
type: fixie-ai/common_voice_17_0
metrics:
- name: Wer
type: wer
value: 75.4221895892105
Whisper Tiny ta
This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4798
- Wer: 75.4222
- Cer: 21.7188
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.04
- training_steps: 5000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.4252 | 0.2 | 1000 | 0.5015 | 76.9190 | 22.6354 |
| 0.4034 | 0.4 | 2000 | 0.4818 | 75.6283 | 21.8341 |
| 0.4708 | 1.1734 | 3000 | 0.4798 | 75.1697 | 21.4852 |
| 0.4435 | 1.3734 | 4000 | 0.4797 | 75.3011 | 21.6158 |
| 0.457 | 2.1468 | 5000 | 0.4798 | 75.4222 | 21.7188 |
Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
Citation
Please cite the model using the following BibTeX entry:
@misc{deepdml/whisper-tiny-ta-mix-norm-opti,
title={Fine-tuned Whisper tiny ASR model for speech recognition in Tamil},
author={Jimenez, David},
howpublished={\url{https://huggingface.co/deepdml/whisper-tiny-ta-mix-norm-opti}},
year={2026}
}