metadata
language:
- es
license: apache-2.0
base_model: openai/whisper-base
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper base Spanish Improved
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: es
split: test
args: 'config: es, split: test'
metrics:
- name: Wer
type: wer
value: 22.17060837943242
Whisper base Spanish Improved
This model is a fine-tuned version of openai/whisper-base on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2940
- Wer: 22.1706
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: 5e-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: 8000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3981 | 0.12 | 1000 | 0.4923 | 28.2216 |
| 0.3628 | 0.25 | 2000 | 0.4366 | 25.6041 |
| 0.4008 | 0.38 | 3000 | 0.4076 | 24.6159 |
| 0.2844 | 0.5 | 4000 | 0.3698 | 27.3086 |
| 0.3651 | 0.62 | 5000 | 0.3469 | 21.5056 |
| 0.3037 | 0.75 | 6000 | 0.3244 | 20.3408 |
| 0.2162 | 0.88 | 7000 | 0.3053 | 24.8691 |
| 0.3015 | 1.0 | 8000 | 0.2940 | 22.1706 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1
- Datasets 2.15.0
- Tokenizers 0.15.0