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--- |
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library_name: transformers |
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language: |
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- jw |
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license: apache-2.0 |
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base_model: openai/whisper-tiny |
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tags: |
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- generated_from_trainer |
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datasets: |
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- SEACrowd/jv_id_tts |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Tiny Java - HQ TTS |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: jv_id_tts |
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type: SEACrowd/jv_id_tts |
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config: jv_id_tts_source |
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split: None |
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args: 'config: jw, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 20.152640264026402 |
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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 Tiny Java - HQ TTS |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the jv_id_tts dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3168 |
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- Wer: 20.1526 |
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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: 3.75e-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: Use OptimizerNames.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: 100 |
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- training_steps: 2500 |
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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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| 0.3173 | 1.7123 | 500 | 0.4364 | 30.1774 | |
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| 0.0564 | 3.4247 | 1000 | 0.3388 | 22.7929 | |
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| 0.0202 | 5.1370 | 1500 | 0.3240 | 20.8746 | |
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| 0.0055 | 6.8493 | 2000 | 0.3174 | 20.4620 | |
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| 0.003 | 8.5616 | 2500 | 0.3168 | 20.1526 | |
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### Framework versions |
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- Transformers 4.51.3 |
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- Pytorch 2.7.0+cu126 |
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- Datasets 2.18.0 |
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- Tokenizers 0.21.1 |
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