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---
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library_name: transformers
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language:
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- multilingual
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license: apache-2.0
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base_model: openai/whisper-tiny.en
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tags:
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- generated_from_trainer
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datasets:
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- arkanalexei/bisix_su_id_reset
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metrics:
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- wer
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model-index:
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- name: 'BisiX: Sundanese Whisper (Reset Params)'
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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: SU ID ASR
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type: arkanalexei/bisix_su_id_reset
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config: su_id_asr_source
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split: validation
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args: su_id_asr_source
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metrics:
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- name: Wer
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type: wer
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value: 100.0
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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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# BisiX: Sundanese Whisper (Reset Params)
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This model is a fine-tuned version of [openai/whisper-tiny.en](https://huggingface.co/openai/whisper-tiny.en) on the SU ID ASR dataset.
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It achieves the following results on the evaluation set:
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- Loss: 10.8462
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- Wer: 100.0
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- Cer: 100.0
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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: 64
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- eval_batch_size: 64
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 128
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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: 30
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- training_steps: 150
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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 | Cer |
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|:-------------:|:------:|:----:|:---------------:|:---------:|:---------:|
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| 10.856 | 0.3529 | 30 | 10.8546 | 1611.8562 | 2230.5547 |
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| 10.853 | 0.7059 | 60 | 10.8517 | 100.0 | 83.0372 |
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| 10.8498 | 1.0588 | 90 | 10.8486 | 100.0 | 95.0543 |
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| 10.8475 | 1.4118 | 120 | 10.8467 | 100.0 | 100.0 |
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| 10.8463 | 1.7647 | 150 | 10.8462 | 100.0 | 100.0 |
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### Framework versions
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- Transformers 4.45.1
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- Pytorch 2.4.1+cu124
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- Datasets 3.0.1
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- Tokenizers 0.20.0
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