metadata
language:
- es
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Es - Spanish
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
args: 'config: es, split: test'
metrics:
- name: Wer
type: wer
value: 13.333333333333334
Whisper Small Es - Spanish
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1798
- Wer: 13.3333
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: 50
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.6172 | 0.1 | 100 | 0.6200 | 107.3958 |
| 0.2709 | 0.21 | 200 | 0.3492 | 67.0833 |
| 0.2839 | 0.31 | 300 | 0.2959 | 40.7292 |
| 0.2876 | 0.41 | 400 | 0.2766 | 29.5833 |
| 0.2296 | 0.52 | 500 | 0.2375 | 17.3958 |
| 0.2649 | 0.62 | 600 | 0.2102 | 15.3125 |
| 0.2644 | 0.72 | 700 | 0.1957 | 17.3958 |
| 0.2384 | 0.82 | 800 | 0.1886 | 13.7500 |
| 0.2325 | 0.93 | 900 | 0.1811 | 13.6458 |
| 0.1374 | 1.03 | 1000 | 0.1798 | 13.3333 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0