--- 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](https://huggingface.co/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: ```bibtex @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} } ```