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Whisper-Small-Ctejarat

Automatic Speech Recognition
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Safetensors
Persian
whisper
fa-asr
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Whisper-Small-Ctejarat / README.md
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metadata
language:
  - fa
license: apache-2.0
base_model: makhataei/Whisper-Small-Ctejarat
tags:
  - fa-asr
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: Whisper Small Persian
    results: []

Whisper Small Persian

This model is a fine-tuned version of makhataei/Whisper-Small-Ctejarat on the Ctejarat dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0031
  • Wer: 13.3353

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-07
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 8
  • 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
  • training_steps: 5000

Training results

Training Loss Epoch Step Validation Loss Wer
0.0032 9.52 100 0.0031 13.1328
0.0027 19.05 200 0.0031 13.0171
0.002 28.57 300 0.0031 13.0171
0.0015 38.1 400 0.0031 13.0749
0.0005 47.62 500 0.0031 13.3642
0.0003 57.14 600 0.0031 13.3353
0.0002 66.67 700 0.0031 13.3353
0.0002 76.19 800 0.0031 13.3353
0.0001 85.71 900 0.0031 13.3063
0.0001 95.24 1000 0.0031 13.3063
0.0001 104.76 1100 0.0031 13.3063
0.0001 114.29 1200 0.0031 13.3931
0.0001 123.81 1300 0.0031 13.3931
0.0001 133.33 1400 0.0031 13.3642
0.0001 142.86 1500 0.0031 13.3931
0.0001 152.38 1600 0.0031 13.3931
0.0001 161.9 1700 0.0031 13.3642
0.0 171.43 1800 0.0031 13.3642
0.0001 180.95 1900 0.0031 13.3642
0.0 190.48 2000 0.0031 13.3642
0.0 200.0 2100 0.0031 13.3642
0.0 209.52 2200 0.0031 13.3642
0.0 219.05 2300 0.0031 13.3642
0.0 228.57 2400 0.0031 13.3642
0.0 238.1 2500 0.0031 13.3353
0.0 247.62 2600 0.0031 13.3353
0.0 257.14 2700 0.0031 13.3353
0.0 266.67 2800 0.0031 13.3353
0.0 276.19 2900 0.0031 13.3353
0.0 285.71 3000 0.0031 13.3353
0.0 295.24 3100 0.0031 13.3353
0.0 304.76 3200 0.0031 13.3353
0.0 314.29 3300 0.0031 13.3642
0.0 323.81 3400 0.0031 13.3642
0.0 333.33 3500 0.0031 13.3642
0.0 342.86 3600 0.0031 13.3642
0.0 352.38 3700 0.0031 13.3353
0.0 361.9 3800 0.0031 13.3353
0.0 371.43 3900 0.0031 13.3353
0.0 380.95 4000 0.0031 13.3353
0.0 390.48 4100 0.0031 13.3353
0.0 400.0 4200 0.0031 13.3353
0.0 409.52 4300 0.0031 13.3353
0.0 419.05 4400 0.0031 13.3353
0.0 428.57 4500 0.0031 13.3353
0.0 438.1 4600 0.0031 13.3353
0.0 447.62 4700 0.0031 13.3353
0.0 457.14 4800 0.0031 13.3353
0.0 466.67 4900 0.0031 13.3353
0.0 476.19 5000 0.0031 13.3353

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.0.1+cu117
  • Datasets 2.15.0
  • Tokenizers 0.15.0