Hugging Face's logo

arun100
/
whisper-base-ar-1

Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Arabic
whisper
whisper-event
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Metrics Community
whisper-base-ar-1 / README.md
arun100's picture
arun100
End of training
b24ec72 verified
preview code
|
raw
history blame
3.15 kB
metadata
language:
  - ar
license: apache-2.0
base_model: openai/whisper-base
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_16_0
metrics:
  - wer
model-index:
  - name: Whisper Base Arabic
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_16_0 ar
          type: mozilla-foundation/common_voice_16_0
          config: ar
          split: test
          args: ar
        metrics:
          - name: Wer
            type: wer
            value: 80.47772163527792

Whisper Base Arabic

This model is a fine-tuned version of openai/whisper-base on the mozilla-foundation/common_voice_16_0 ar dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5856
  • Wer: 80.4777

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: 5e-07
  • 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
  • training_steps: 10000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.7392 1.53 500 0.8623 100.8133
0.5938 3.07 1000 0.7397 93.6651
0.5388 4.6 1500 0.6953 92.3005
0.4982 6.13 2000 0.6682 88.9392
0.4795 7.67 2500 0.6512 90.1524
0.4483 9.2 3000 0.6373 87.1234
0.4374 10.74 3500 0.6261 85.3144
0.4331 12.27 4000 0.6179 86.4290
0.4125 13.8 4500 0.6106 83.2865
0.3984 15.34 5000 0.6059 83.0676
0.4035 16.87 5500 0.6008 82.2165
0.3997 18.4 6000 0.5970 81.1195
0.3878 19.94 6500 0.5941 81.7153
0.3827 21.47 7000 0.5906 81.2559
0.3785 23.01 7500 0.5892 81.0506
0.372 24.54 8000 0.5882 81.4248
0.3655 26.07 8500 0.5865 81.0479
0.3697 27.61 9000 0.5856 80.4777
0.3658 29.14 9500 0.5849 80.6128
0.3539 30.67 10000 0.5848 80.6696

Framework versions

  • Transformers 4.37.0.dev0
  • Pytorch 2.1.2+cu121
  • Datasets 2.16.2.dev0
  • Tokenizers 0.15.0