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metadata
library_name: transformers
language:
  - multilingual
license: apache-2.0
base_model: openai/whisper-tiny.en
tags:
  - generated_from_trainer
datasets:
  - arkanalexei/bisix_su_id_reset
metrics:
  - wer
model-index:
  - name: 'BisiX: Sundanese Whisper (Reset Params)'
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: SU ID ASR
          type: arkanalexei/bisix_su_id_reset
          config: su_id_asr_source
          split: validation
          args: su_id_asr_source
        metrics:
          - name: Wer
            type: wer
            value: 100

BisiX: Sundanese Whisper (Reset Params)

This model is a fine-tuned version of openai/whisper-tiny.en on the SU ID ASR dataset. It achieves the following results on the evaluation set:

  • Loss: 10.8462
  • Wer: 100.0
  • Cer: 100.0

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 1e-05
  • train_batch_size: 64
  • eval_batch_size: 64
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 30
  • training_steps: 150
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer
10.856 0.3529 30 10.8546 1611.8562 2230.5547
10.853 0.7059 60 10.8517 100.0 83.0372
10.8498 1.0588 90 10.8486 100.0 95.0543
10.8475 1.4118 120 10.8467 100.0 100.0
10.8463 1.7647 150 10.8462 100.0 100.0

Framework versions

  • Transformers 4.45.1
  • Pytorch 2.4.1+cu124
  • Datasets 3.0.1
  • Tokenizers 0.20.0