metadata
language:
- es
license: apache-2.0
base_model: openai/whisper-large
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Large Spanish
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_13_0 es
type: mozilla-foundation/common_voice_13_0
config: es
split: test
args: es
metrics:
- name: Wer
type: wer
value: 5.126477928109984
Whisper Large Spanish
This model is a fine-tuned version of openai/whisper-large on the mozilla-foundation/common_voice_13_0 es dataset. It achieves the following results on the evaluation set:
- Loss: 0.2663
- Wer: 5.1265
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: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 20000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0834 | 2.0 | 1000 | 0.1862 | 6.3852 |
| 0.0871 | 4.0 | 2000 | 0.1777 | 5.9175 |
| 0.039 | 6.0 | 3000 | 0.1780 | 5.7423 |
| 0.0265 | 8.0 | 4000 | 0.2121 | 5.7744 |
| 0.0059 | 10.0 | 5000 | 0.2219 | 5.8097 |
| 0.0855 | 12.01 | 6000 | 0.1839 | 5.9778 |
| 0.0037 | 14.01 | 7000 | 0.2273 | 5.8565 |
| 0.0293 | 16.01 | 8000 | 0.1965 | 5.8078 |
| 0.1174 | 18.01 | 9000 | 0.1984 | 5.8893 |
| 0.0355 | 20.01 | 10000 | 0.2136 | 5.8662 |
| 0.0279 | 22.01 | 11000 | 0.1882 | 5.4960 |
| 0.0043 | 24.01 | 12000 | 0.2444 | 5.3356 |
| 0.0302 | 26.01 | 13000 | 0.2223 | 5.4620 |
| 0.0011 | 28.01 | 14000 | 0.2603 | 5.5608 |
| 0.001 | 30.01 | 15000 | 0.2452 | 5.3087 |
| 0.0003 | 32.01 | 16000 | 0.2573 | 5.3523 |
| 0.0004 | 34.02 | 17000 | 0.2690 | 5.2952 |
| 0.0013 | 36.02 | 18000 | 0.2373 | 5.1438 |
| 0.0004 | 38.02 | 19000 | 0.2618 | 5.1361 |
| 0.0004 | 40.02 | 20000 | 0.2663 | 5.1265 |
Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3