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--- |
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library_name: peft |
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language: |
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- ro |
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license: apache-2.0 |
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base_model: openai/whisper-small |
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tags: |
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- base_model:adapter:openai/whisper-small |
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- lora |
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- transformers |
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datasets: |
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- VladS159/romanian_speech_dataset_with_5_percent_synthetic_data |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small Ro - PEFT |
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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: Romanian Speech Dataset + 5% Synthetic |
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type: VladS159/romanian_speech_dataset_with_5_percent_synthetic_data |
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metrics: |
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- type: wer |
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value: 106.59810174871058 |
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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 Small Ro - PEFT |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Romanian Speech Dataset + 5% Synthetic dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4248 |
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- Wer: 106.5981 |
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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: 0.001 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 100 |
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- training_steps: 100 |
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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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| 2.0921 | 0.0113 | 50 | 1.0811 | 95.9014 | |
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| 0.6328 | 0.0227 | 100 | 0.4248 | 106.5981 | |
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### Framework versions |
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- PEFT 0.18.1.dev0 |
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- Transformers 4.57.1 |
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- Pytorch 2.9.1+rocm6.4 |
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- Datasets 3.6.0 |
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- Tokenizers 0.22.1 |
