metadata
language:
- tr
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
metrics:
- wer
model-index:
- name: Whisper Small TR - tgrhn
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 16.1
type: mozilla-foundation/common_voice_16_1
config: tr
split: None
args: 'config: tr, split: test'
metrics:
- name: Wer
type: wer
value: 20.934495462305687
Whisper Small TR - tgrhn
This model is a fine-tuned version of openai/whisper-small on the Common Voice 16.1 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3657
- Wer: 20.9345
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: 1.25e-05
- train_batch_size: 128
- eval_batch_size: 64
- 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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0855 | 2.92 | 1000 | 0.2497 | 21.0261 |
| 0.0143 | 5.83 | 2000 | 0.2964 | 21.4700 |
| 0.0026 | 8.75 | 3000 | 0.3394 | 20.9597 |
| 0.0012 | 11.66 | 4000 | 0.3584 | 20.9201 |
| 0.0009 | 14.58 | 5000 | 0.3657 | 20.9345 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2