metadata
language:
- tr
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
metrics:
- wer
model-index:
- name: Whisper Large TR - Özgün Tosun
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: 11.727918051936383
Whisper Large TR - Özgün Tosun
This model is a fine-tuned version of openai/whisper-large-v3 on the Common Voice 16.1 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1323
- Wer: 11.7279
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: 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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1372 | 0.3652 | 1000 | 0.1810 | 16.0805 |
| 0.1103 | 0.7305 | 2000 | 0.1628 | 14.5458 |
| 0.0563 | 1.0957 | 3000 | 0.1513 | 12.9302 |
| 0.0657 | 1.4609 | 4000 | 0.1383 | 12.4198 |
| 0.0444 | 1.8262 | 5000 | 0.1323 | 11.7279 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1