This model is a fine-tuned version of openai/whisper-large-v3-turbo on the audiofolder dataset. It achieves the following results on the evaluation set:

Loss: 0.0096
Wer: 1.1101

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 1000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0097	6.3694	1000	0.0096	1.1101

Framework versions

Transformers 4.45.2
Pytorch 2.0.1+cu117
Datasets 3.0.1
Tokenizers 0.20.1

smrc/fr-qc-turbo

fr-qc-turbo

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

smrc/
fr-qc-turbo