metadata
library_name: transformers
language:
- ig
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Tiny Igbo - Benjamin Ogbonna
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Whisper for Igbo 1.0
type: mozilla-foundation/common_voice_11_0
config: ig
split: None
args: 'config: ig, split: test'
metrics:
- name: Wer
type: wer
value: 100
Whisper Tiny Igbo - Benjamin Ogbonna
This model is a fine-tuned version of openai/whisper-tiny on the Whisper for Igbo 1.0 dataset. It achieves the following results on the evaluation set:
- Loss: 5.9958
- Wer: 100.0
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: 3e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.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: 25
- training_steps: 300
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0 | 50.0 | 50 | 4.6220 | 100.0 |
| 0.0 | 100.0 | 100 | 5.1929 | 105.7143 |
| 0.0 | 150.0 | 150 | 5.5613 | 108.5714 |
| 0.0 | 200.0 | 200 | 5.8296 | 97.1429 |
| 0.0 | 250.0 | 250 | 5.9560 | 100.0 |
| 0.0 | 300.0 | 300 | 5.9958 | 100.0 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1