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metadata
base_model: masoudmzb/wav2vec2-xlsr-multilingual-53-fa
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: wav2vec2-large-xlsr-persian-asr-shemo_partial
    results: []

wav2vec2-large-xlsr-persian-asr-shemo_partial

This model is a fine-tuned version of masoudmzb/wav2vec2-xlsr-multilingual-53-fa on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8069
  • Wer: 0.3490

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: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 2000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
2.3226 0.62 100 1.4548 0.4851
1.7166 1.25 200 1.2460 0.4279
1.4987 1.88 300 1.0671 0.4194
1.3771 2.5 400 0.9784 0.4054
1.3217 3.12 500 0.9450 0.3905
1.3272 3.75 600 0.8851 0.3841
1.3025 4.38 700 0.8748 0.3779
1.2719 5.0 800 0.8674 0.3724
1.2563 5.62 900 0.8467 0.3692
1.2451 6.25 1000 0.8440 0.3645
1.2585 6.88 1100 0.8292 0.3610
1.2633 7.5 1200 0.8137 0.3601
1.1923 8.12 1300 0.8263 0.3575
1.2349 8.75 1400 0.8184 0.3551
1.2511 9.38 1500 0.8078 0.3516
1.1779 10.0 1600 0.8102 0.3505
1.2161 10.62 1700 0.8123 0.3499
1.1967 11.25 1800 0.8086 0.3502
1.2454 11.88 1900 0.8066 0.3490
1.1928 12.5 2000 0.8069 0.3490

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu118
  • Datasets 2.15.0
  • Tokenizers 0.15.0