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--- |
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library_name: transformers |
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language: |
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- sq |
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license: apache-2.0 |
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base_model: openai/whisper-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- Kushtrim/audioshqip |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Base Shqip |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: Audio Shqip 97 orë |
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type: Kushtrim/audioshqip |
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args: 'config: sq, split: test' |
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metrics: |
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- type: wer |
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value: 40.143396979133186 |
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name: Wer |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Whisper Base Shqip |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co./openai/whisper-base) on the Audio Shqip 97 orë dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5274 |
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- Wer: 40.1434 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- training_steps: 10000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:------:|:-----:|:---------------:|:-------:| |
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| 1.0357 | 0.3249 | 500 | 1.0437 | 70.9649 | |
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| 0.7862 | 0.6498 | 1000 | 0.7759 | 57.9971 | |
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| 0.6561 | 0.9747 | 1500 | 0.6805 | 51.6728 | |
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| 0.5704 | 1.2995 | 2000 | 0.6337 | 49.0896 | |
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| 0.5511 | 1.6244 | 2500 | 0.5968 | 47.4252 | |
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| 0.522 | 1.9493 | 3000 | 0.5740 | 47.2168 | |
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| 0.4252 | 2.2742 | 3500 | 0.5612 | 43.5865 | |
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| 0.4411 | 2.5991 | 4000 | 0.5487 | 43.2817 | |
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| 0.4434 | 2.9240 | 4500 | 0.5373 | 43.3737 | |
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| 0.3791 | 3.2489 | 5000 | 0.5353 | 42.3143 | |
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| 0.371 | 3.5737 | 5500 | 0.5297 | 41.3114 | |
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| 0.4173 | 3.8986 | 6000 | 0.5231 | 41.4012 | |
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| 0.3009 | 4.2235 | 6500 | 0.5276 | 40.9756 | |
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| 0.3337 | 4.5484 | 7000 | 0.5249 | 40.4393 | |
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| 0.3145 | 4.8733 | 7500 | 0.5222 | 40.2154 | |
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| 0.2897 | 5.1982 | 8000 | 0.5264 | 40.4925 | |
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| 0.2717 | 5.5231 | 8500 | 0.5256 | 40.6387 | |
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| 0.2947 | 5.8480 | 9000 | 0.5251 | 40.2753 | |
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| 0.2933 | 6.1728 | 9500 | 0.5268 | 40.5601 | |
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| 0.2644 | 6.4977 | 10000 | 0.5274 | 40.1434 | |
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### Framework versions |
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- Transformers 4.45.2 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.20.3 |
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