pashto-asr-cws-v1 / README.md
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metadata
license: apache-2.0
base_model: steja/whisper-small-persian
tags:
  - generated_from_trainer
datasets:
  - fleurs
metrics:
  - wer
model-index:
  - name: pashto-asr-cws-v1
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: fleurs
          type: fleurs
          config: ps_af
          split: None
          args: ps_af
        metrics:
          - name: Wer
            type: wer
            value: 49.37953995157385

pashto-asr-cws-v1

This model is a fine-tuned version of steja/whisper-small-persian on the fleurs dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7501
  • Wer: 49.3795
  • Cer: 20.8766

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-05
  • train_batch_size: 32
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 30
  • training_steps: 1000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer
0.7899 0.8065 100 0.8629 75.8323 47.9045
0.5051 1.6129 200 0.6860 52.9888 23.1242
0.3555 2.4194 300 0.6612 51.6798 22.9404
0.257 3.2258 400 0.6565 49.2660 21.0588
0.2174 4.0323 500 0.6560 47.1777 19.8523
0.1626 4.8387 600 0.6787 48.7591 20.4305
0.1268 5.6452 700 0.7062 49.4401 21.0137
0.0871 6.4516 800 0.7279 49.2433 20.7062
0.0685 7.2581 900 0.7443 49.3795 21.2276
0.0662 8.0645 1000 0.7501 49.3795 20.8766

Framework versions

  • Transformers 4.42.4
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1