metadata
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: whisper-small-dv
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_13_0
type: common_voice_13_0
config: dv
split: test
args: dv
metrics:
- name: Wer
type: wer
value: 11.072086796258302
whisper-small-dv
This model is a fine-tuned version of openai/whisper-small on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2738
- Wer Ortho: 56.8842
- Wer: 11.0721
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 3000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.1237 | 1.63 | 500 | 0.1702 | 63.0963 | 13.1429 |
| 0.0494 | 3.26 | 1000 | 0.1662 | 57.8592 | 11.6285 |
| 0.0315 | 4.89 | 1500 | 0.1894 | 58.3397 | 11.3937 |
| 0.0121 | 6.51 | 2000 | 0.2257 | 57.7756 | 11.5502 |
| 0.005 | 8.14 | 2500 | 0.2643 | 56.9747 | 11.1573 |
| 0.0056 | 9.77 | 3000 | 0.2738 | 56.8842 | 11.0721 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.0
- Tokenizers 0.13.3