--- language: - ta license: apache-2.0 tags: - generated_from_trainer datasets: - mozilla-foundation/common_voice_13_0 metrics: - wer base_model: openai/whisper-small model-index: - name: carl-whisper-small-finetuned-tamil results: - task: type: automatic-speech-recognition name: Automatic Speech Recognition dataset: name: Common Voice 13 type: mozilla-foundation/common_voice_13_0 config: ta split: None args: ta metrics: - type: wer value: 21.830330026321118 name: Wer widgets: - label: "Sample Audio 1" audio: "https://yourdomain.com/path/to/sample1.wav" - label: "Sample Audio 2" audio: "https://yourdomain.com/path/to/sample2.wav" --- # carl-whisper-small-finetuned-tamil This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 13 dataset. It achieves the following results on the evaluation set: - Loss: 0.4660 - Wer Ortho: 62.9625 - Wer: 21.8303 ## 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: 10 - training_steps: 100 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | |:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:| | 0.3504 | 0.37 | 100 | 0.4660 | 62.9625 | 21.8303 | ### Framework versions - Transformers 4.38.2 - Pytorch 1.11.0+cu102 - Datasets 2.18.0 - Tokenizers 0.15.2