metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: openai/whisper-small
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_11_0
type: common_voice_11_0
config: tr
split: test
args: tr
metrics:
- name: Wer
type: wer
value: 16.318103103769815
openai/whisper-small
This model is a fine-tuned version of openai/whisper-small on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2860
- Wer: 16.3181
- Cer: 4.1450
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: 8
- 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: 500
- training_steps: 20000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.1563 | 1.0 | 2500 | 0.2524 | 19.8570 | 5.1738 |
| 0.032 | 2.01 | 5000 | 0.2567 | 18.5627 | 4.7793 |
| 0.013 | 3.01 | 7500 | 0.2637 | 17.7723 | 4.6664 |
| 0.0057 | 4.02 | 10000 | 0.2703 | 17.0596 | 4.3662 |
| 0.0012 | 5.02 | 12500 | 0.2696 | 17.8322 | 5.2286 |
| 0.003 | 6.03 | 15000 | 0.2800 | 16.7200 | 4.2972 |
| 0.0003 | 7.03 | 17500 | 0.2834 | 16.4091 | 4.2018 |
| 0.0002 | 8.04 | 20000 | 0.2860 | 16.3181 | 4.1450 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2