metadata
language:
- tr
license: apache-2.0
base_model: openai/whisper-base
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
metrics:
- wer
model-index:
- name: Whisper Base Turkish
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_16_0 tr
type: mozilla-foundation/common_voice_16_0
config: tr
split: test
args: tr
metrics:
- name: Wer
type: wer
value: 30.362728902323294
Whisper Base Turkish
This model is a fine-tuned version of openai/whisper-base on the mozilla-foundation/common_voice_16_0 tr dataset. It achieves the following results on the evaluation set:
- Loss: 0.4280
- Wer: 30.3627
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-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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 |
|---|---|---|---|---|
| 0.4162 | 1.03 | 500 | 0.5339 | 35.4346 |
| 0.3776 | 2.06 | 1000 | 0.4788 | 33.4892 |
| 0.3238 | 4.02 | 1500 | 0.4568 | 31.9497 |
| 0.2714 | 5.06 | 2000 | 0.4469 | 31.4277 |
| 0.3232 | 7.02 | 2500 | 0.4386 | 31.0991 |
| 0.2324 | 8.05 | 3000 | 0.4353 | 30.7406 |
| 0.2953 | 10.01 | 3500 | 0.4306 | 30.6035 |
| 0.2878 | 11.04 | 4000 | 0.4292 | 30.4278 |
| 0.3077 | 13.01 | 4500 | 0.4286 | 30.4155 |
| 0.2914 | 14.04 | 5000 | 0.4280 | 30.3627 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0