metadata
language:
- es
license: apache-2.0
base_model: openai/whisper-medium
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Medium 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: 5.408751772230669
Whisper Medium Spanish
This model is a fine-tuned version of openai/whisper-medium on the mozilla-foundation/common_voice_13_0 es dataset. It achieves the following results on the evaluation set:
- Loss: 0.1915
- Wer: 5.4088
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: 64
- eval_batch_size: 32
- 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: 10000
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.0917 | 2.0 | 1000 | 0.1944 | 6.8560 |
0.0927 | 4.0 | 2000 | 0.1817 | 6.1439 |
0.0456 | 6.01 | 3000 | 0.1805 | 6.2626 |
0.0343 | 8.01 | 4000 | 0.2097 | 6.1773 |
0.0046 | 10.01 | 5000 | 0.2292 | 5.9374 |
0.0829 | 12.01 | 6000 | 0.1814 | 6.0644 |
0.0021 | 14.01 | 7000 | 0.2318 | 5.7096 |
0.0288 | 16.01 | 8000 | 0.1871 | 5.5755 |
0.1297 | 18.02 | 9000 | 0.1831 | 5.6885 |
0.0377 | 20.02 | 10000 | 0.1915 | 5.4088 |
Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3