Whisper Base Sna Cleaned Duration Sortagrad
This model is a fine-tuned version of openai/whisper-base on the Cleaned Google WAXAL Shona dataset. It achieves the following results on the evaluation set: Loss: 0.4571 Wer: 40.7137
Fonte do modelo
- Tipo
- Text model
- Tamanho do arquivo
- 277 MB
- Modelo base
- openai/whisper-base
- Versão
- vmodel
- Atualizado
- 26 de out. de 2026
- Downloads
- 12
- Fonte
- Hugging Face
Descrição da fonte
Whisper Medium Shona - Cleaned Data Duration SortaGrad
This model is a fine-tuned version of openai/whisper-base on the Cleaned Google WAXAL Shona dataset. It achieves the following results on the evaluation set:
- Loss: 0.4571
- Wer: 40.7137
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: 8
- seed: 42
- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.8798 | 0.2398 | 200 | 0.9193 | 63.5934 |
| 0.6167 | 0.4796 | 400 | 0.6583 | 50.7509 |
| 0.5866 | 0.7194 | 600 | 0.5679 | 49.3659 |
| 0.5302 | 0.9592 | 800 | 0.5203 | 45.3494 |
| 0.4440 | 1.1990 | 1000 | 0.4967 | 43.8557 |
| 0.4213 | 1.4388 | 1200 | 0.4814 | 42.0742 |
| 0.4077 | 1.6787 | 1400 | 0.4709 | 42.3322 |
| 0.4016 | 1.9185 | 1600 | 0.4619 | 41.7158 |
| 0.3498 | 2.1583 | 1800 | 0.4586 | 40.7164 |
| 0.3882 | 2.3981 | 2000 | 0.4571 | 40.7137 |
Framework versions
- Transformers 5.13.1
- Pytorch 2.12.0+cu130
- Datasets 5.0.0
- Tokenizers 0.22.2
Fontes
1 fonte
Fontes
1 fonteVerificado 26 de out.
Artefatos de modelo
1 artefato
Artefatos de modelo
1 artefatoTrechos de fonte
3 trechos
Trechos de fonte
3 trechos--- library_name: transformers language: - sna license: apache-2.0 base_model: openai/whisper-base tags: - generated_from_trainer metrics: - wer model-index: - name: Whisper Medium Shona - Cleaned Data Duration SortaGrad results: [] --- <!-- 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. --> # Whisper Medium Shona - Cleaned Data Duration SortaGrad This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Cleaned Google WAXAL Shona dataset. It achieves the following results on the evaluation set: - Loss: 0.4571 - Wer: 40.7137 ## 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: 8 - seed: 42 - optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 200 - training_steps: 2000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:----:|:---------------:|:-------:| | 0.8798 | 0.2398 | 200 | 0.9193 | 63.5934 | | 0.6167 | 0.4796 | 400 | 0.6583 | 50.7509 | | 0.5866 | 0.7194 | 600 | 0.5679 | 49.3659 | | 0.5302 | 0.9592 | 800 | 0.5203 | 45.3494 | | 0.4440 | 1.1990 | 1000 | 0.4967 | 43.8557 | | 0.4213 | 1.4388 | 1200 | 0.4814 | 42.0742 | | 0.4077 | 1.6787 | 1400 | 0.4709 | 42.3322 | | 0.4016 | 1.9185 | 1600 | 0.4619 | 41.7158 | | 0.3498 | 2.1583 | 1800 | 0.4586 | 40.7164 | | 0.3882 | 2.3981 | 2000 | 0.4571 | 40.7137 | ### Framework versions - Transformers 5.13.1 - Pytorch 2.12.0+cu130 - Datasets 5.0.0 - Tokenizers 0.22.2
Source context: 12 downloads · 0 likes · Pipeline automatic-speech-recognition · Library transformers · Repo CasperMuz/whisper-base-sna-cleaned-duration-sortagrad
Source context: 24 downloads · 0 likes · Pipeline automatic-speech-recognition · Library transformers · Repo CasperMuz/whisper-base-sna-cleaned-duration-sortagrad
