metadata
library_name: transformers
language:
- tr
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Large V3 Pro Turkish - Evren Ozkip
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 13
type: mozilla-foundation/common_voice_13_0
config: tr
split: test
args: tr
metrics:
- name: Wer
type: wer
value: 31.350330500472147
Whisper Large V3 Pro on the Turkish Dataset - Evren Ozkip
This model is a fine-tuned version of openai/whisper-small on the Turkish Common Voice 13 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4715
- Wer Ortho: 35.2262
- Wer: 31.3503
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| No log | 0.08 | 20 | 0.3358 | 25.0241 | 21.7186 |
| 0.4294 | 0.16 | 40 | 0.3339 | 26.0828 | 22.7573 |
| 0.2121 | 0.24 | 60 | 0.5079 | 54.9567 | 50.1416 |
| 0.3798 | 0.32 | 80 | 0.4675 | 55.2454 | 50.8026 |
| 0.3469 | 0.4 | 100 | 0.4715 | 35.2262 | 31.3503 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.1.1+cu121
- Datasets 3.6.0
- Tokenizers 0.21.1