readme: ---
  tags:
  - automatic-speech-recognition
  - abdusahmbzuai/arabic_speech_massive_300hrs
  - generated_from_trainer
  model-index:
  - name: aradia-ctc-hubert-ft
    results: []
  ---
  
  <!-- 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. -->
  
  # aradia-ctc-hubert-ft
  
  This model is a fine-tuned version of [/l/users/abdulwahab.sahyoun/aradia/aradia-ctc-hubert-ft](https://huggingface.co//l/users/abdulwahab.sahyoun/aradia/aradia-ctc-hubert-ft) on the ABDUSAHMBZUAI/ARABIC_SPEECH_MASSIVE_300HRS - NA dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8536
  - Wer: 0.3737
  
  ## 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: 30.0
  - 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 | 0.7177          | 0.4010 |
  | 0.3919        | 14.78 | 3400 | 0.6888          | 0.4043 |
  | 0.3767        | 15.22 | 3500 | 0.7124          | 0.4202 |
  | 0.3767        | 15.65 | 3600 | 0.7276          | 0.4120 |
  | 0.3767        | 16.09 | 3700 | 0.7265          | 0.4034 |
  | 0.3767        | 16.52 | 3800 | 0.7392          | 0.4077 |
  | 0.3767        | 16.95 | 3900 | 0.7403          | 0.3965 |
  | 0.3603        | 17.39 | 4000 | 0.7445          | 0.4016 |
  | 0.3603        | 17.82 | 4100 | 0.7579          | 0.4012 |
  | 0.3603        | 18.26 | 4200 | 0.7225          | 0.3963 |
  | 0.3603        | 18.69 | 4300 | 0.7355          | 0.3951 |
  | 0.3603        | 19.13 | 4400 | 0.7482          | 0.3925 |
  | 0.3153        | 19.56 | 4500 | 0.7723          | 0.3972 |
  | 0.3153        | 20.0  | 4600 | 0.7469          | 0.3898 |
  | 0.3153        | 20.43 | 4700 | 0.7800          | 0.3944 |
  | 0.3153        | 20.87 | 4800 | 0.7827          | 0.3897 |
  | 0.3153        | 21.3  | 4900 | 0.7935          | 0.3914 |
  | 0.286         | 21.74 | 5000 | 0.7984          | 0.3750 |
  | 0.286         | 22.17 | 5100 | 0.7945          | 0.3830 |
  | 0.286         | 22.61 | 5200 | 0.8011          | 0.3775 |
  | 0.286         | 23.04 | 5300 | 0.7978          | 0.3824 |
  | 0.286         | 23.48 | 5400 | 0.8161          | 0.3833 |
  | 0.2615        | 23.91 | 5500 | 0.7823          | 0.3858 |
  | 0.2615        | 24.35 | 5600 | 0.8312          | 0.3863 |
  | 0.2615        | 24.78 | 5700 | 0.8427          | 0.3819 |
  | 0.2615        | 25.22 | 5800 | 0.8432          | 0.3802 |
  | 0.2615        | 25.65 | 5900 | 0.8286          | 0.3794 |
  | 0.2408      