metadata
library_name: transformers
license: apache-2.0
base_model: Leonel-Maia/fongbe-whisper-small
tags:
- generated_from_trainer
datasets:
- Leonel-Maia/ewe_dataset
metrics:
- wer
model-index:
- name: whisper-small-tf
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Leonel-Maia/ewe_dataset
type: Leonel-Maia/ewe_dataset
metrics:
- name: Wer
type: wer
value: 0.3810818307905687
whisper-small-tf
This model is a fine-tuned version of Leonel-Maia/fongbe-whisper-small on the Leonel-Maia/ewe_dataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.4403
- Wer: 0.3811
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: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Use adamw_torch 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: 500
- num_epochs: 60.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4849 | 1.7564 | 500 | 0.4948 | 0.4388 |
| 0.3147 | 3.5101 | 1000 | 0.4403 | 0.3811 |
| 0.1881 | 5.2639 | 1500 | 0.4694 | 0.3843 |
| 0.124 | 7.0176 | 2000 | 0.5287 | 0.3952 |
| 0.05 | 8.7740 | 2500 | 0.6124 | 0.4024 |
| 0.0166 | 10.5277 | 3000 | 0.6773 | 0.3989 |
| 0.0083 | 12.2814 | 3500 | 0.7468 | 0.4017 |
Framework versions
- Transformers 4.50.3
- Pytorch 2.7.0+cu126
- Datasets 3.5.0
- Tokenizers 0.21.1