--- tags: - generated_from_trainer datasets: - afrispeech-200 metrics: - wer model-index: - name: whisper-small-hi-2400_500_133 results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: afrispeech-200 type: afrispeech-200 config: hausa split: train args: hausa metrics: - name: Wer type: wer value: 0.32728583443469905 --- # whisper-small-hi-2400_500_133 This model is a fine-tuned version of [saif-daoud/whisper-small-hi-2400_500_132](https://huggingface.co/saif-daoud/whisper-small-hi-2400_500_132) on the afrispeech-200 dataset. It achieves the following results on the evaluation set: - Loss: 0.7843 - Wer: 0.3273 ## 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-06 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 150 - training_steps: 540 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:------:| | 0.9568 | 0.5 | 270 | 0.7916 | 0.3298 | | 0.9337 | 1.5 | 540 | 0.7843 | 0.3273 | ### Framework versions - Transformers 4.28.0.dev0 - Pytorch 1.13.1+cu116 - Datasets 2.11.0 - Tokenizers 0.13.2