This model is a fine-tuned version of openai/whisper-medium on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:

Loss: 0.5798
Wer Ortho: 11.4657
Cer Ortho: 3.2862
Wer: 6.9420
Cer: 2.3005

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: 2
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 32
total_train_batch_size: 64
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: 5
training_steps: 50
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Cer Ortho	Wer	Cer
2.9481	0.2	10	1.7270	12.0729	3.6802	7.1193	2.5784
1.3731	0.4	20	1.0923	11.5624	3.3599	6.9948	2.3544
0.9897	0.6	30	0.8008	11.6923	3.3918	7.0571	2.3674
0.7372	0.8	40	0.6473	11.4720	3.3122	6.9293	2.3112
0.6275	1.0	50	0.5798	11.4657	3.2862	6.9420	2.3005

Framework versions

Transformers 4.53.2
Pytorch 2.6.0+cu124
Datasets 2.14.4
Tokenizers 0.21.2

mmarron14/whisper-medium-cv17-es-50-steps

Whisper Medium CV17 Es 50 steps- María Marrón

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

mmarron14/
whisper-medium-cv17-es-50-steps