This model is a fine-tuned version of openai/whisper-small on the OpenSLR Chilean Spanish dataset. It achieves the following results on the evaluation set:

Loss: 0.1276
Wer: 4.8044

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: 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: 500
training_steps: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0009	8.6207	1000	0.1144	5.1588
0.0002	17.2414	2000	0.1197	4.8569
0.0001	25.8621	3000	0.1254	4.8307
0.0001	34.4828	4000	0.1276	4.8044

Framework versions

Transformers 4.48.3
Pytorch 2.9.1+cpu
Datasets 3.6.0
Tokenizers 0.21.4

rcastrovexler/whisper-small-es-cl-2

Whisper Small ES-CL - Roberto Castro-Vexler - wintrained

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

rcastrovexler/
whisper-small-es-cl-2