metadata
language:
- es
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- facebook/multilingual_librispeech
metrics:
- wer
model-index:
- name: Whisper Medium es - Dash Guitar
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: facebook/multilingual_librispeech
type: facebook/multilingual_librispeech
config: spanish
split: test
args: spanish
metrics:
- name: Wer
type: wer
value: 7.085875706214689
Whisper Medium es - Dash Guitar
This model is a fine-tuned version of openai/whisper-small on the facebook/multilingual_librispeech dataset. It achieves the following results on the evaluation set:
- Loss: 0.1535
- Wer Ortho: 7.0848
- Wer: 7.0859
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: 8
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.3349 | 0.02 | 500 | 0.1782 | 8.1526 | 8.1571 |
| 0.309 | 0.04 | 1000 | 0.1702 | 7.5899 | 7.5921 |
| 0.2814 | 0.05 | 1500 | 0.1680 | 8.0103 | 8.0124 |
| 0.3067 | 0.07 | 2000 | 0.1665 | 8.1007 | 8.1028 |
| 0.3223 | 0.09 | 2500 | 0.1751 | 9.2272 | 9.2294 |
| 0.2696 | 0.11 | 3000 | 0.1583 | 7.2374 | 7.2395 |
| 0.3203 | 0.13 | 3500 | 0.1542 | 6.9560 | 6.9559 |
| 0.2655 | 0.14 | 4000 | 0.1535 | 7.0848 | 7.0859 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.16.1
- Tokenizers 0.15.0