metadata
library_name: transformers
language:
- sq
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- generated_from_trainer
datasets:
- Kushtrim/audioshqip
metrics:
- wer
model-index:
- name: Whisper Large v3 Turbo Shqip
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Audio Shqip 50 orë
type: Kushtrim/audioshqip
args: 'config: sq, split: test'
metrics:
- type: wer
value: 26.29520403254481
name: Wer
Whisper Large v3 Turbo Shqip
This model is a fine-tuned version of openai/whisper-large-v3-turbo on the Audio Shqip 50 orë dataset. It achieves the following results on the evaluation set:
- Loss: 0.5501
- Wer: 26.2952
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: 8
- 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: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.5589 | 0.5363 | 500 | 0.5765 | 40.2773 |
| 0.391 | 1.0727 | 1000 | 0.4633 | 32.9234 |
| 0.3557 | 1.6090 | 1500 | 0.4209 | 32.8188 |
| 0.2288 | 2.1453 | 2000 | 0.4132 | 30.0056 |
| 0.237 | 2.6817 | 2500 | 0.4012 | 29.9073 |
| 0.1776 | 3.2180 | 3000 | 0.4055 | 30.2650 |
| 0.1838 | 3.7544 | 3500 | 0.4034 | 29.6501 |
| 0.1328 | 4.2907 | 4000 | 0.4109 | 29.3719 |
| 0.1301 | 4.8270 | 4500 | 0.4052 | 28.7716 |
| 0.1034 | 5.3634 | 5000 | 0.4231 | 27.3180 |
| 0.0845 | 5.8997 | 5500 | 0.4296 | 27.5167 |
| 0.0857 | 6.4360 | 6000 | 0.4526 | 26.9750 |
| 0.0526 | 6.9724 | 6500 | 0.4550 | 27.2343 |
| 0.0436 | 7.5087 | 7000 | 0.4833 | 27.2824 |
| 0.0284 | 8.0451 | 7500 | 0.4983 | 26.5734 |
| 0.0328 | 8.5814 | 8000 | 0.5043 | 26.8244 |
| 0.0164 | 9.1177 | 8500 | 0.5225 | 26.5441 |
| 0.0171 | 9.6541 | 9000 | 0.5318 | 26.2659 |
| 0.019 | 10.1904 | 9500 | 0.5473 | 26.3182 |
| 0.0253 | 10.7267 | 10000 | 0.5501 | 26.2952 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3