metadata
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- abdouaziiz/wolof_lam_asr
metrics:
- wer
model-index:
- name: whisper-m-wo
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: abdouaziiz/wolof_lam_asr
type: abdouaziiz/wolof_lam_asr
metrics:
- name: Wer
type: wer
value: 0.2595195074616877
whisper-m-wo
This model is a fine-tuned version of openai/whisper-medium on the abdouaziiz/wolof_lam_asr dataset. It achieves the following results on the evaluation set:
- Loss: 0.4811
- Wer: 0.2595
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: 8
- 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: 40
- training_steps: 16000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.7816 | 0.3912 | 1000 | 0.7274 | 0.6369 |
| 0.6368 | 0.7825 | 2000 | 0.6093 | 0.5042 |
| 0.3921 | 1.1737 | 3000 | 0.5506 | 0.4280 |
| 0.3494 | 1.5649 | 4000 | 0.5247 | 0.3115 |
| 0.3264 | 1.9562 | 5000 | 0.4907 | 0.3293 |
| 0.1734 | 2.3474 | 6000 | 0.4968 | 0.2973 |
| 0.1808 | 2.7387 | 7000 | 0.4811 | 0.2595 |
| 0.1064 | 3.1299 | 8000 | 0.4989 | 0.2490 |
| 0.0802 | 3.5211 | 9000 | 0.4975 | 0.2275 |
| 0.0745 | 3.9124 | 10000 | 0.4883 | 0.2429 |
Framework versions
- Transformers 4.43.3
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1