metadata
language:
- tr
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Medium Tr - Can K V2
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 17.0
type: mozilla-foundation/common_voice_17_0
config: tr
split: test
args: 'config: tr, split: test'
metrics:
- name: Wer
type: wer
value: 67.02546197734821
Whisper Medium Tr - Can K V2
This model is a fine-tuned version of openai/whisper-medium on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1892
- Wer: 67.0255
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
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 8000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.146 | 0.34 | 1000 | 0.2164 | 105.0754 |
| 0.1562 | 0.69 | 2000 | 0.2115 | 43.5238 |
| 0.0803 | 1.03 | 3000 | 0.1979 | 42.8919 |
| 0.0668 | 1.38 | 4000 | 0.1944 | 37.3397 |
| 0.0693 | 1.72 | 5000 | 0.1869 | 36.3910 |
| 0.0305 | 2.07 | 6000 | 0.1898 | 49.8254 |
| 0.0272 | 2.41 | 7000 | 0.1908 | 60.8005 |
| 0.0274 | 2.76 | 8000 | 0.1892 | 67.0255 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.13.3