metadata
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- common_voice_16_0
metrics:
- wer
model-index:
- name: whisper-base-common-voice-16-pt-v8
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_16_0
type: common_voice_16_0
config: pt
split: test
args: pt
metrics:
- name: Wer
type: wer
value: 26.192630898513254
whisper-base-common-voice-16-pt-v8
This model is a fine-tuned version of openai/whisper-base on the common_voice_16_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4574
- Wer: 26.1926
- Wer Normalized: 20.0029
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 16
- 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: 7000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Wer Normalized |
|---|---|---|---|---|---|
| 0.4883 | 0.74 | 1000 | 0.3803 | 28.0317 | 21.8327 |
| 0.2659 | 1.48 | 2000 | 0.3677 | 26.3688 | 20.1666 |
| 0.1251 | 2.22 | 3000 | 0.3730 | 26.3752 | 20.4620 |
| 0.1071 | 2.96 | 4000 | 0.3867 | 25.5026 | 19.5470 |
| 0.0523 | 3.7 | 5000 | 0.4148 | 25.7094 | 19.6851 |
| 0.02 | 4.44 | 6000 | 0.4491 | 25.6803 | 19.5759 |
| 0.0134 | 5.18 | 7000 | 0.4574 | 26.1926 | 20.0029 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.1
- Datasets 2.16.1
- Tokenizers 0.15.0