Whisper Tiny Hausa3

--- library_name: transformers language: - ha license: apache-2.0 base_model: EYEDOL/whisper-tiny-hausa2 tags: - generated_from_trainer datasets: - EYEDOL/naija-voices-hausa-split_0-6 metrics: - wer model-index: - name: EYEDOL/whisper-tiny-hausa3 results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: EYEDOL/naija-voices-hausa-split_0-6 type: EYEDOL/naija-voices-hausa-split_0-6 metrics: - name: Wer type: wer value: 0.43485342019543977 --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # EYEDOL/whisper-tiny-hausa3 This model is a fine-tuned version of [EYEDOL/whisper-tiny-hausa2](https://huggingface.co/EYEDOL/whisper-tiny-hausa2) on the EYEDOL/naija-voices-hausa-split_0-6 dataset. It achieves the following results on the evaluation set: - Loss: 0.6238 - Wer Ortho: 0.5015 - Wer: 0.4349 ## 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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: constant_with_warmup - lr_scheduler_warmup_steps: 0.1 - num_epochs: 3 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:| | 1.2512 | 1.0 | 665 | 0.6263 | 0.5023 | 0.4362 | | 1.1143 | 2.0 | 1330 | 0.6204 | 0.4940 | 0.4280 | | 1.0009 | 3.0 | 1995 | 0.6238 | 0.5015 | 0.4349 | ### Framework versions - Transformers 5.0.0 - Pytorch 2.10.0+cu128 - Datasets 4.8.3 - Tokenizers 0.22.2