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ghofrani
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common7

Automatic Speech Recognition
Transformers
PyTorch
Persian
wav2vec2
mozilla-foundation/common_voice_7_0
Generated from Trainer
Inference Endpoints
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common7 / README.md
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metadata
language:
  - fa
tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_7_0
  - generated_from_trainer
datasets:
  - common_voice
model-index:
  - name: common7
    results: []

common7

This model is a fine-tuned version of common7/checkpoint-4000 on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - FA dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3428
  • Wer: 0.3493

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: 6e-05
  • train_batch_size: 32
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 123.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
2.957 3.29 500 2.9503 1.0
1.7225 6.58 1000 0.8860 0.7703
1.4907 9.86 1500 0.6555 0.6673
1.4177 13.16 2000 0.5784 0.6076
1.3425 16.45 2500 0.5379 0.5718
1.33 19.73 3000 0.4962 0.5245
1.4378 23.03 3500 0.4699 0.5098
1.1894 26.31 4000 0.4527 0.4848
1.1844 29.6 4500 0.4309 0.4651
1.1795 32.89 5000 0.4131 0.4524
1.1471 36.18 5500 0.4052 0.4435
1.1337 39.47 6000 0.3927 0.4363
1.1896 42.76 6500 0.3811 0.4254
1.1847 46.05 7000 0.3855 0.4129
0.9954 49.34 7500 0.3729 0.3981
1.0293 52.63 8000 0.3637 0.4014
1.0224 55.92 8500 0.3578 0.3885
1.012 59.21 9000 0.3629 0.3930
1.0772 62.5 9500 0.3635 0.3906
1.0344 65.79 10000 0.3469 0.3771
0.9457 69.08 10500 0.3435 0.3735
0.9307 72.37 11000 0.3519 0.3762
0.9523 75.65 11500 0.3443 0.3666
0.9523 78.94 12000 0.3502 0.3757
0.9475 82.24 12500 0.3509 0.3643
0.9971 85.52 13000 0.3502 0.3626
0.9058 88.81 13500 0.3472 0.3605
0.8922 92.1 14000 0.3530 0.3618
0.9 95.39 14500 0.3500 0.3574
0.9051 98.68 15000 0.3456 0.3535
0.9304 101.97 15500 0.3438 0.3578
0.9433 105.26 16000 0.3396 0.3530
0.8988 108.55 16500 0.3436 0.3539
0.8789 111.84 17000 0.3426 0.3516
0.8667 115.13 17500 0.3438 0.3506
0.8895 118.42 18000 0.3434 0.3503
0.8888 121.71 18500 0.3425 0.3494

Framework versions

  • Transformers 4.17.0.dev0
  • Pytorch 1.10.2
  • Datasets 1.18.3.dev0
  • Tokenizers 0.10.3