metadata

library_name: transformers
language:
  - es
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - ylacombe/google-chilean-spanish
metrics:
  - wer
model-index:
  - name: Whisper Small ES-CL - Roberto Castro-Vexler
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: OpenSLR Chilean Spanish
          type: ylacombe/google-chilean-spanish
          args: 'config: es-cl, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 5.930960948953752

Whisper Small ES-CL - Roberto Castro-Vexler

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: 0.1552
Wer: 5.9310

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: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0038	8.6207	1000	0.1381	6.1975
0.0002	17.2414	2000	0.1466	5.8510
0.0001	25.8621	3000	0.1528	5.9709
0.0001	34.4828	4000	0.1552	5.9310

Framework versions

Transformers 4.45.2
Pytorch 2.4.1+cu121
Datasets 3.0.1
Tokenizers 0.20.1