metadata
language:
- es
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Large v2 Spanish
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_11_0 es
type: mozilla-foundation/common_voice_11_0
config: es
split: test
args: es
metrics:
- name: Wer
type: wer
value: 5.288186684683748
Whisper Large v2 Spanish
This model is a fine-tuned version of openai/whisper-large-v2 on the mozilla-foundation/common_voice_11_0 es dataset. It achieves the following results on the evaluation set:
- Loss: 0.1702
- Wer google/fleurs: 4.89
- Wer mozilla-foundation/common_voice_11_0: 5.2882
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: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1738 | 0.1 | 1000 | 0.2031 | 7.0384 |
| 0.2108 | 1.01 | 2000 | 0.1885 | 6.6668 |
| 0.1599 | 1.11 | 3000 | 0.1814 | 6.5342 |
| 0.0794 | 2.01 | 4000 | 0.1792 | 6.0314 |
| 0.0477 | 2.11 | 5000 | 0.1936 | 6.1795 |
| 0.0341 | 3.02 | 6000 | 0.2038 | 6.0113 |
| 0.0264 | 3.12 | 7000 | 0.2111 | 5.8410 |
| 0.0608 | 4.02 | 8000 | 0.1824 | 5.9067 |
| 0.0523 | 4.12 | 9000 | 0.1768 | 5.3941 |
| 0.0984 | 5.03 | 10000 | 0.1702 | 5.2882 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 2.0.0.dev20221210+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2