| ---
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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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| ---
|
|
|
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| should probably proofread and complete it, then remove this comment. -->
|
|
|
| # BisiX: Sundanese Whisper (Reset Params)
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|
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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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|
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| ## Model description
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| More information needed
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|
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| ## Intended uses & limitations
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|
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| More information needed
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|
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| ## Training and evaluation data
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|
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| More information needed
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|
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| ## Training procedure
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|
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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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|
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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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|
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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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|
