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: 0.3184
Wer Ortho: 12.5020
Wer: 7.0621

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
training_steps: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
No log	0.2	1	0.6327	12.5828	7.1257
No log	0.4	2	0.5409	12.3581	7.0316
No log	0.6	3	0.4270	12.3989	7.0393
No log	0.8	4	0.3494	12.4352	7.0431
No log	1.0	5	0.3184	12.5020	7.0621

Framework versions

Transformers 4.53.2
Pytorch 2.9.1+cu128
Datasets 2.14.4
Tokenizers 0.21.4

mmarron14/whisper-medium-cv17-es-5-steps_sin_proc-def4

Whisper Medium CV17 Es 5 steps without processing of text -same configuration of training as 5-steps_sin_proc, but with filtering 30sec- María Marrón

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

mmarron14/
whisper-medium-cv17-es-5-steps_sin_proc-def4