metadata
library_name: transformers
language:
- wo
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- Google/Fleurs
metrics:
- wer
model-index:
- name: Whisper-WOLOF-10-hours-Google-Fleurs-dataset
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Wolof Google Fleurs
type: Google/Fleurs
config: wo_sn
split: None
args: 'config: wo_sn, split: test'
metrics:
- name: Wer
type: wer
value: 44.91918164349497
Whisper-WOLOF-10-hours-Google-Fleurs-dataset
This model is a fine-tuned version of openai/whisper-small on the Wolof Google Fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 1.4961
- Wer: 44.9192
- Cer: 16.7830
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 1.1589 | 6.4935 | 500 | 1.0397 | 46.6260 | 18.8906 |
| 0.0602 | 12.9870 | 1000 | 1.2600 | 46.1173 | 17.4588 |
| 0.0042 | 19.4805 | 1500 | 1.3654 | 44.8401 | 16.6024 |
| 0.0013 | 25.9740 | 2000 | 1.4186 | 44.7383 | 16.5644 |
| 0.0007 | 32.4675 | 2500 | 1.4569 | 45.2922 | 17.2179 |
| 0.0006 | 38.9610 | 3000 | 1.4812 | 44.9531 | 16.6603 |
| 0.0005 | 45.4545 | 3500 | 1.4961 | 44.9192 | 16.7830 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.1.0+cu118
- Datasets 3.0.1
- Tokenizers 0.20.1