Whisper Base Shqip
This model is a fine-tuned version of openai/whisper-base on the Audio Shqip 39 orë dataset. It achieves the following results on the evaluation set:
- Loss: 0.6632
- Wer: 47.3566
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: 7000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.0935 | 0.6369 | 500 | 1.0589 | 76.5520 |
| 0.7452 | 1.2739 | 1000 | 0.8016 | 60.4529 |
| 0.6676 | 1.9108 | 1500 | 0.7127 | 54.2641 |
| 0.5127 | 2.5478 | 2000 | 0.6744 | 51.1191 |
| 0.464 | 3.1847 | 2500 | 0.6519 | 49.6937 |
| 0.4283 | 3.8217 | 3000 | 0.6346 | 48.3889 |
| 0.3729 | 4.4586 | 3500 | 0.6371 | 47.7377 |
| 0.3281 | 5.0955 | 4000 | 0.6373 | 47.8776 |
| 0.3163 | 5.7325 | 4500 | 0.6376 | 47.7256 |
| 0.2713 | 6.3694 | 5000 | 0.6487 | 47.7039 |
| 0.2862 | 7.0064 | 5500 | 0.6461 | 47.1757 |
| 0.2487 | 7.6433 | 6000 | 0.6572 | 46.9997 |
| 0.2526 | 8.2803 | 6500 | 0.6628 | 47.2818 |
| 0.2087 | 8.9172 | 7000 | 0.6632 | 47.3566 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Base model
openai/whisper-base