metadata
language:
- tr
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Medium Turkish
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_11_0 tr
type: mozilla-foundation/common_voice_11_0
config: tr
split: test
args: tr
metrics:
- name: Wer
type: wer
value: 11.068934102641968
Whisper Medium Turkish
This model is a fine-tuned version of openai/whisper-medium on the mozilla-foundation/common_voice_11_0 tr dataset. It achieves the following results on the evaluation set:
- Loss: 0.2780
- Wer: 11.0689
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: 32
- eval_batch_size: 16
- 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 |
|---|---|---|---|---|
| 0.0742 | 1.07 | 1000 | 0.2104 | 12.3975 |
| 0.0345 | 3.02 | 2000 | 0.2182 | 11.6573 |
| 0.0103 | 4.09 | 3000 | 0.2489 | 11.7921 |
| 0.0018 | 6.04 | 4000 | 0.2657 | 11.0746 |
| 0.0005 | 7.11 | 5000 | 0.2780 | 11.0689 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2