--- language: - sw license: apache-2.0 tags: - whisper-event - generated_from_trainer datasets: - mozilla-foundation/common_voice_11_0 metrics: - wer model-index: - name: Whisper Small Swahili results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: mozilla-foundation/common_voice_11_0 sw type: mozilla-foundation/common_voice_11_0 config: sw split: test args: sw metrics: - name: Wer type: wer value: 23.724554196406032 --- # Whisper Small Swahili This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 sw dataset. It achieves the following results on the evaluation set: - Loss: 0.6442 - Wer: 23.7246 ## 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: 32 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 5000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.2694 | 1.07 | 1000 | 0.5438 | 26.8354 | | 0.2306 | 3.02 | 2000 | 0.5081 | 23.9231 | | 0.0467 | 4.09 | 3000 | 0.5648 | 24.4085 | | 0.0239 | 6.03 | 4000 | 0.5994 | 23.8634 | | 0.0123 | 7.1 | 5000 | 0.6442 | 23.7246 | ### Framework versions - Transformers 4.30.0.dev0 - Pytorch 2.0.1+cu117 - Datasets 2.12.1.dev0 - Tokenizers 0.13.3