metadata
language:
- es
license: apache-2.0
base_model: openai/whisper-base
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Base 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: 13.531181636803376
Whisper Base Spanish
This model is a fine-tuned version of openai/whisper-base on the mozilla-foundation/common_voice_13_0 es dataset. It achieves the following results on the evaluation set:
- Loss: 0.3281
- Wer: 13.5312
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: 2.5e-05
- train_batch_size: 128
- eval_batch_size: 64
- 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: 5000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2173 | 4.0 | 1000 | 0.3409 | 14.8123 |
| 0.0955 | 8.01 | 2000 | 0.3377 | 15.4269 |
| 0.1647 | 12.01 | 3000 | 0.3393 | 14.5602 |
| 0.0986 | 16.01 | 4000 | 0.3281 | 13.5312 |
| 0.1272 | 20.02 | 5000 | 0.3423 | 13.7596 |
Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3