metadata
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: vi_whisper-small
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Vivos + Commonvoice
type: vivos
config: None
split: None
metrics:
- name: Wer
type: wer
value: 21.8855
vi_whisper-small
This model is a fine-tuned version of openai/whisper-small on the Mixing of Vivos and CommonVoice dataset. It achieves the following results on the evaluation set:
- Loss: 0.2894
- Wer: 21.8855
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
In training phase i used VIVOS dataset and cleaned CommonVoice The VIVOS evaluation dataset was used
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 8000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.249 | 1.1 | 1000 | 0.3766 | 32.1678 |
| 0.1416 | 2.2 | 2000 | 0.2881 | 46.4646 |
| 0.0839 | 3.3 | 3000 | 0.2799 | 22.7791 |
| 0.0546 | 4.41 | 4000 | 0.2894 | 21.8855 |
| 0.0256 | 5.51 | 5000 | 0.3023 | 32.2973 |
| 0.0111 | 6.61 | 6000 | 0.3061 | 31.0153 |
| 0.0028 | 7.71 | 7000 | 0.3143 | 27.1691 |
| 0.0014 | 8.81 | 8000 | 0.3187 | 27.3634 |
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3