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 115 orë
type: Kushtrim/audioshqip
args: 'config: sq, split: test'
metrics:
- type: wer
value: 22.006858788533318
name: Wer
Whisper Large v3 Turbo Shqip
This model is a fine-tuned version of openai/whisper-large-v3-turbo on the Audio Shqip 115 orë dataset. It achieves the following results on the evaluation set:
- Loss: 0.3322
- Wer: 22.0069
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 |
|---|---|---|---|---|
| 0.5211 | 0.2738 | 500 | 0.5221 | 36.9257 |
| 0.4152 | 0.5476 | 1000 | 0.4144 | 31.1469 |
| 0.3847 | 0.8215 | 1500 | 0.3747 | 28.2953 |
| 0.2703 | 1.0953 | 2000 | 0.3536 | 26.4348 |
| 0.2471 | 1.3691 | 2500 | 0.3419 | 25.5897 |
| 0.2691 | 1.6429 | 3000 | 0.3293 | 24.5533 |
| 0.2426 | 1.9168 | 3500 | 0.3202 | 24.5742 |
| 0.1993 | 2.1906 | 4000 | 0.3178 | 23.5548 |
| 0.204 | 2.4644 | 4500 | 0.3124 | 23.6609 |
| 0.2 | 2.7382 | 5000 | 0.3098 | 23.5131 |
| 0.1298 | 3.0120 | 5500 | 0.3101 | 22.5753 |
| 0.1213 | 3.2859 | 6000 | 0.3145 | 23.0129 |
| 0.1343 | 3.5597 | 6500 | 0.3105 | 22.6511 |
| 0.1341 | 3.8335 | 7000 | 0.3076 | 22.3479 |
| 0.0895 | 4.1073 | 7500 | 0.3210 | 22.3593 |
| 0.0883 | 4.3812 | 8000 | 0.3223 | 22.4786 |
| 0.0892 | 4.6550 | 8500 | 0.3182 | 22.1073 |
| 0.0937 | 4.9288 | 9000 | 0.3179 | 21.9008 |
| 0.0608 | 5.2026 | 9500 | 0.3326 | 22.0466 |
| 0.0482 | 5.4765 | 10000 | 0.3322 | 22.0069 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3