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vanilla-whisper-tiny_tat_evaluated_on_condenser

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metadata
language:
  - zh
license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - generated_from_trainer
datasets:
  - formospeech/tat_asr_aligned
model-index:
  - name: Whisper Tiny Taiwanese Condenser
    results: []

Whisper Tiny Taiwanese Condenser

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

  • eval_loss: 0.4231
  • eval_cer: 9.3916
  • eval_runtime: 1392.366
  • eval_samples_per_second: 4.033
  • eval_steps_per_second: 0.126
  • step: 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: 0.0001
  • train_batch_size: 64
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 681
  • training_steps: 6810
  • mixed_precision_training: Native AMP

Framework versions

  • Transformers 4.42.3
  • Pytorch 2.3.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1