metadata
library_name: transformers
language:
- sq
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- Kushtrim/audioshqip
metrics:
- wer
model-index:
- name: Whisper Base Shqip
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Audio Shqip 97 orë
type: Kushtrim/audioshqip
args: 'config: sq, split: test'
metrics:
- type: wer
value: 40.143396979133186
name: Wer
Whisper Base Shqip
This model is a fine-tuned version of openai/whisper-base on the Audio Shqip 97 orë dataset. It achieves the following results on the evaluation set:
- Loss: 0.5274
- Wer: 40.1434
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: 16
- eval_batch_size: 8
- 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: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.0357 | 0.3249 | 500 | 1.0437 | 70.9649 |
| 0.7862 | 0.6498 | 1000 | 0.7759 | 57.9971 |
| 0.6561 | 0.9747 | 1500 | 0.6805 | 51.6728 |
| 0.5704 | 1.2995 | 2000 | 0.6337 | 49.0896 |
| 0.5511 | 1.6244 | 2500 | 0.5968 | 47.4252 |
| 0.522 | 1.9493 | 3000 | 0.5740 | 47.2168 |
| 0.4252 | 2.2742 | 3500 | 0.5612 | 43.5865 |
| 0.4411 | 2.5991 | 4000 | 0.5487 | 43.2817 |
| 0.4434 | 2.9240 | 4500 | 0.5373 | 43.3737 |
| 0.3791 | 3.2489 | 5000 | 0.5353 | 42.3143 |
| 0.371 | 3.5737 | 5500 | 0.5297 | 41.3114 |
| 0.4173 | 3.8986 | 6000 | 0.5231 | 41.4012 |
| 0.3009 | 4.2235 | 6500 | 0.5276 | 40.9756 |
| 0.3337 | 4.5484 | 7000 | 0.5249 | 40.4393 |
| 0.3145 | 4.8733 | 7500 | 0.5222 | 40.2154 |
| 0.2897 | 5.1982 | 8000 | 0.5264 | 40.4925 |
| 0.2717 | 5.5231 | 8500 | 0.5256 | 40.6387 |
| 0.2947 | 5.8480 | 9000 | 0.5251 | 40.2753 |
| 0.2933 | 6.1728 | 9500 | 0.5268 | 40.5601 |
| 0.2644 | 6.4977 | 10000 | 0.5274 | 40.1434 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3