metadata
library_name: transformers
language:
- fr
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
datasets:
- ras0k/whisper-rap-queb-v10
metrics:
- wer
model-index:
- name: Whisper Quebec Rap - ras0k
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Genius-Quebec-Rap-Top-500
type: ras0k/whisper-rap-queb-v10
config: default
split: None
args: 'config: fr-FR, split: train'
metrics:
- name: Wer
type: wer
value: 29.88372093023256
Whisper Quebec Rap - ras0k
This model is a fine-tuned version of openai/whisper-large-v3 on the Genius-Quebec-Rap-Top-500 dataset. It achieves the following results on the evaluation set:
- Loss: 0.8482
- Wer: 29.8209
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: 4e-05
- train_batch_size: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 200
- training_steps: 1200
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 0 | 0 | 0.7656 | 58.2465 |
| 0.2658 | 5.8824 | 200 | 0.5356 | 31.8419 |
| 0.0230 | 11.7647 | 400 | 0.7306 | 30.2070 |
| 0.0051 | 17.6471 | 600 | 0.8482 | 29.8209 |
| 0.0044 | 23.5294 | 800 | 0.8627 | 29.9070 |
| 0.0040 | 29.4118 | 1000 | 0.8684 | 30.0140 |
| 0.0042 | 35.2941 | 1200 | 0.8689 | 29.8837 |
Framework versions
- Transformers 5.3.0
- Pytorch 2.10.0+cu128
- Datasets 4.6.1
- Tokenizers 0.22.2