metadata
language:
- tr
license: apache-2.0
base_model: alikanakar/whisper-synthesized-turkish-8-hour
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
metrics:
- wer
model-index:
- name: Whisper Small Turkish Derived
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: 18.625004393518683
Whisper Small Turkish Derived
This model is a fine-tuned version of alikanakar/whisper-synthesized-turkish-8-hour on the mozilla-foundation/common_voice_16_0 tr dataset. It achieves the following results on the evaluation set:
- Loss: 0.2859
- Wer: 18.6250
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: 5e-07
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- 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: 100
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3197 | 0.58 | 200 | 0.3517 | 21.5757 |
| 0.2672 | 1.16 | 400 | 0.3203 | 20.6724 |
| 0.2532 | 1.75 | 600 | 0.3065 | 19.6496 |
| 0.2382 | 2.33 | 800 | 0.2991 | 19.3420 |
| 0.2448 | 2.91 | 1000 | 0.2943 | 19.1276 |
| 0.2197 | 3.49 | 1200 | 0.2909 | 18.9712 |
| 0.2159 | 4.07 | 1400 | 0.2885 | 18.7340 |
| 0.2212 | 4.65 | 1600 | 0.2871 | 18.6988 |
| 0.2114 | 5.24 | 1800 | 0.2861 | 18.6320 |
| 0.2092 | 5.82 | 2000 | 0.2859 | 18.6250 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0