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--- |
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library_name: transformers |
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language: |
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- id |
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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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- generated_from_trainer |
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datasets: |
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- octava/indonesian-voice-transcription-1.4.9a-cv-fl-slrjv-md |
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model-index: |
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- name: Optimized Whisper Small Id for Inspirasi |
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results: [] |
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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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# Optimized Whisper Small Id for Inspirasi |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Extracted Youtube with CommonVoice11, Fleurs, OpenSLR, and MagicData dataset. |
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It achieves the following results on the evaluation set: |
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- eval_loss: 0.3722 |
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- eval_wer: 20.3324 |
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- eval_runtime: 495.0068 |
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- eval_samples_per_second: 3.527 |
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- eval_steps_per_second: 0.222 |
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- epoch: 3.0354 |
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- step: 9000 |
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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: 32 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Use adamw_torch 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: 500 |
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- training_steps: 10000 |
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- mixed_precision_training: Native AMP |
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### Framework versions |
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- Transformers 4.49.0 |
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- Pytorch 2.2.0a0+81ea7a4 |
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- Datasets 3.3.2 |
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- Tokenizers 0.21.0 |
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