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huber_arabic_mdd_v2

Automatic Speech Recognition
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hubert
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metadata
license: apache-2.0
base_model: facebook/hubert-large-ll60k
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: huber_arabic_mdd_v2
    results: []

huber_arabic_mdd_v2

This model is a fine-tuned version of facebook/hubert-large-ll60k on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2858
  • Wer: 0.0564
  • Cer: 0.0459

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: 0.0003
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 20
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer
3.3219 0.9951 102 3.2861 1.0 1.0
3.2152 2.0 205 3.1685 1.0 1.0
2.5507 2.9951 307 2.3708 0.9718 0.9819
0.5766 4.0 410 0.6351 0.2216 0.2046
0.2255 4.9951 512 0.3469 0.0889 0.0740
0.1148 6.0 615 0.3393 0.0776 0.0635
0.1222 6.9951 717 0.3368 0.0688 0.0535
0.075 8.0 820 0.2846 0.0610 0.0479
0.0631 8.9951 922 0.2948 0.0589 0.0453
0.0365 10.0 1025 0.2657 0.0552 0.0432
0.0484 10.9951 1127 0.2631 0.0573 0.0458
0.046 12.0 1230 0.2817 0.0572 0.0462
0.0326 12.9951 1332 0.2807 0.0587 0.0473
0.0379 14.0 1435 0.2682 0.0590 0.0479
0.0328 14.9951 1537 0.2773 0.0545 0.0440
0.0398 16.0 1640 0.2727 0.0576 0.0462
0.0165 16.9951 1742 0.2844 0.0573 0.0466
0.0201 18.0 1845 0.2812 0.0564 0.0455
0.0207 18.9951 1947 0.2860 0.0569 0.0465
0.0194 19.9024 2040 0.2858 0.0564 0.0459

Framework versions

  • Transformers 4.40.0
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.0
  • Tokenizers 0.19.1