metadata
library_name: transformers
language:
- bem
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- BIG-C/BEMBA
metrics:
- wer
model-index:
- name: Whisper Small Bemba - Beijuka Bruno
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: BEMBA
type: BIG-C/BEMBA
args: 'config: bemba, split: test'
metrics:
- name: Wer
type: wer
value: 0.4832828045603997
Whisper Small Bemba - Beijuka Bruno
This model is a fine-tuned version of openai/whisper-small on the BEMBA dataset. It achieves the following results on the evaluation set:
- Loss: 1.3874
- Wer: 0.4833
- Cer: 0.1314
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: 4
- 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: 500
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 1.3572 | 1.0 | 638 | 0.9726 | 0.6131 | 0.2029 |
| 0.7143 | 2.0 | 1276 | 0.8546 | 0.5769 | 0.1907 |
| 0.4485 | 3.0 | 1914 | 0.8472 | 0.5749 | 0.1936 |
| 0.2568 | 4.0 | 2552 | 0.9305 | 0.6149 | 0.1963 |
| 0.1328 | 5.0 | 3190 | 0.9798 | 0.5448 | 0.1658 |
| 0.0678 | 6.0 | 3828 | 1.0441 | 0.5373 | 0.1647 |
| 0.0366 | 7.0 | 4466 | 1.1153 | 0.5366 | 0.1719 |
| 0.0223 | 8.0 | 5104 | 1.1549 | 0.5441 | 0.1626 |
| 0.0169 | 9.0 | 5742 | 1.2010 | 0.5364 | 0.1698 |
| 0.0122 | 10.0 | 6380 | 1.2321 | 0.5384 | 0.1560 |
| 0.0098 | 11.0 | 7018 | 1.2646 | 0.5202 | 0.1522 |
| 0.0092 | 12.0 | 7656 | 1.2855 | 0.5279 | 0.1570 |
| 0.0085 | 13.0 | 8294 | 1.3001 | 0.5218 | 0.1568 |
| 0.0094 | 14.0 | 8932 | 1.3090 | 0.5240 | 0.1573 |
| 0.008 | 15.0 | 9570 | 1.3016 | 0.5220 | 0.1524 |
| 0.0064 | 16.0 | 10208 | 1.3748 | 0.5195 | 0.1532 |
| 0.0061 | 17.0 | 10846 | 1.3741 | 0.5147 | 0.1561 |
| 0.0072 | 18.0 | 11484 | 1.3958 | 0.5211 | 0.1560 |
| 0.007 | 19.0 | 12122 | 1.3849 | 0.5233 | 0.1554 |
| 0.0042 | 20.0 | 12760 | 1.4370 | 0.5124 | 0.1521 |
| 0.0046 | 21.0 | 13398 | 1.4660 | 0.5177 | 0.1529 |
| 0.0048 | 22.0 | 14036 | 1.4625 | 0.5115 | 0.1509 |
| 0.0057 | 23.0 | 14674 | 1.4502 | 0.5197 | 0.1554 |
| 0.005 | 24.0 | 15312 | 1.4473 | 0.5174 | 0.1568 |
| 0.0037 | 25.0 | 15950 | 1.4782 | 0.5258 | 0.1545 |
| 0.0035 | 26.0 | 16588 | 1.4798 | 0.5154 | 0.1533 |
| 0.0034 | 27.0 | 17226 | 1.5074 | 0.5170 | 0.1539 |
| 0.0042 | 28.0 | 17864 | 1.4976 | 0.5227 | 0.1572 |
| 0.0045 | 29.0 | 18502 | 1.5364 | 0.5110 | 0.1565 |
| 0.0025 | 30.0 | 19140 | 1.5072 | 0.5206 | 0.1545 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.1.0+cu118
- Datasets 3.0.0
- Tokenizers 0.19.1