metadata
library_name: transformers
language:
- tl
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Small Tagalog - Bob
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: fleurs_fil_ph
type: google/fleurs
config: fil_ph
split: None
args: 'config: fil_ph, split: test'
metrics:
- name: Wer
type: wer
value: 16.655684328849958
Whisper Small Tagalog - Bob
This model is a fine-tuned version of openai/whisper-small on the fleurs_fil_ph dataset. It achieves the following results on the evaluation set:
- Loss: 0.4392
- Wer: 16.6557
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 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: 50
- training_steps: 1200
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2302 | 1.6949 | 200 | 0.3983 | 19.2837 |
| 0.0482 | 3.3898 | 400 | 0.3991 | 18.2875 |
| 0.017 | 5.0847 | 600 | 0.4136 | 16.8805 |
| 0.0068 | 6.7797 | 800 | 0.4265 | 16.5355 |
| 0.0038 | 8.4746 | 1000 | 0.4357 | 16.6557 |
| 0.0031 | 10.1695 | 1200 | 0.4392 | 16.6557 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.2.1+cu121
- Datasets 3.5.0
- Tokenizers 0.21.1