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abdusah
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aradia-ctc-hubert-ft

Automatic Speech Recognition
Transformers
PyTorch
hubert
abdusahmbzuai/arabic_speech_massive_300hrs
Generated from Trainer
Inference Endpoints
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aradia-ctc-hubert-ft / README.md
Abdulwahab Sahyoun
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metadata
license: apache-2.0
tags:
  - automatic-speech-recognition
  - abdusahmbzuai/arabic_speech_massive_300hrs
  - generated_from_trainer
model-index:
  - name: aradia-ctc-hubert-ft
    results: []

aradia-ctc-hubert-ft

This model is a fine-tuned version of facebook/hubert-large-ll60k on the ABDUSAHMBZUAI/ARABIC_SPEECH_MASSIVE_300HRS - NA dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6946
  • Wer: 0.3940

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: 32
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 15.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
No log 0.43 100 3.6934 1.0
No log 0.87 200 3.0763 1.0
No log 1.3 300 2.9737 1.0
No log 1.74 400 2.5734 1.0
5.0957 2.17 500 1.1900 0.9011
5.0957 2.61 600 0.9726 0.7572
5.0957 3.04 700 0.8960 0.6209
5.0957 3.48 800 0.7851 0.5515
5.0957 3.91 900 0.7271 0.5115
1.0312 4.35 1000 0.7053 0.4955
1.0312 4.78 1100 0.6823 0.4737
1.0312 5.22 1200 0.6768 0.4595
1.0312 5.65 1300 0.6635 0.4488
1.0312 6.09 1400 0.6602 0.4390
0.6815 6.52 1500 0.6464 0.4310
0.6815 6.95 1600 0.6455 0.4394
0.6815 7.39 1700 0.6630 0.4312
0.6815 7.82 1800 0.6521 0.4126
0.6815 8.26 1900 0.6282 0.4284
0.544 8.69 2000 0.6248 0.4178
0.544 9.13 2100 0.6510 0.4104
0.544 9.56 2200 0.6527 0.4013
0.544 10.0 2300 0.6511 0.4064
0.544 10.43 2400 0.6734 0.4061
0.4478 10.87 2500 0.6756 0.4145
0.4478 11.3 2600 0.6727 0.3990
0.4478 11.74 2700 0.6619 0.4007
0.4478 12.17 2800 0.6614 0.4019
0.4478 12.61 2900 0.6695 0.4004
0.3919 13.04 3000 0.6778 0.3966
0.3919 13.48 3100 0.6872 0.3971
0.3919 13.91 3200 0.6882 0.3945
0.3919 14.35 3300 0.6938 0.3937
0.3919 14.78 3400 0.6928 0.3946

Framework versions

  • Transformers 4.18.0.dev0
  • Pytorch 1.10.2+cu113
  • Datasets 1.18.4
  • Tokenizers 0.11.6