metadata
library_name: transformers
language:
- yo
license: apache-2.0
base_model: EYEDOL/whisper-tiny-yoruba1
tags:
- generated_from_trainer
datasets:
- EYEDOL/naija-voices-yoruba-split_0-5
metrics:
- wer
model-index:
- name: EYEDOL/whisper-tiny-yoruba2
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: EYEDOL/naija-voices-yoruba-split_0-5
type: EYEDOL/naija-voices-yoruba-split_0-5
metrics:
- name: Wer
type: wer
value: 0.6604725510764774
EYEDOL/whisper-tiny-yoruba2
This model is a fine-tuned version of EYEDOL/whisper-tiny-yoruba1 on the EYEDOL/naija-voices-yoruba-split_0-5 dataset. It achieves the following results on the evaluation set:
- Loss: 0.8206
- Wer Ortho: 0.7328
- Wer: 0.6605
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: 12
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 1.4647 | 1.0 | 583 | 0.7470 | 0.7172 | 0.6312 |
| 1.4031 | 2.0 | 1166 | 0.7409 | 0.7386 | 0.6564 |
| 1.3010 | 3.0 | 1749 | 0.7406 | 0.7229 | 0.6421 |
| 1.2136 | 4.0 | 2332 | 0.7384 | 0.7477 | 0.6644 |
| 1.1362 | 5.0 | 2915 | 0.7413 | 0.7877 | 0.7124 |
| 1.0626 | 6.0 | 3498 | 0.7462 | 0.7162 | 0.6332 |
| 0.9947 | 7.0 | 4081 | 0.7573 | 0.7547 | 0.6707 |
| 0.9314 | 8.0 | 4664 | 0.7624 | 0.7062 | 0.6266 |
| 0.8680 | 9.0 | 5247 | 0.7747 | 0.7211 | 0.6416 |
| 0.8080 | 10.0 | 5830 | 0.7881 | 0.7519 | 0.6641 |
| 0.7481 | 11.0 | 6413 | 0.8032 | 0.7310 | 0.6519 |
| 0.6922 | 12.0 | 6996 | 0.8206 | 0.7328 | 0.6605 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.3
- Tokenizers 0.22.2