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wav2vec2-common_voice-tr-output

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the COMMON_VOICE - TR dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3776
  • Wer: 0.3243

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: 0.0003
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 20.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
No log 0.92 100 3.6020 1.0
No log 1.83 200 2.9971 0.9999
No log 2.75 300 0.9174 0.7772
No log 3.67 400 0.5668 0.6356
3.1619 4.59 500 0.4949 0.5256
3.1619 5.5 600 0.4516 0.4744
3.1619 6.42 700 0.4291 0.4575
3.1619 7.34 800 0.4330 0.4273
3.1619 8.26 900 0.4016 0.4145
0.2261 9.17 1000 0.4214 0.4005
0.2261 10.09 1100 0.4093 0.3946
0.2261 11.01 1200 0.4051 0.3917
0.2261 11.93 1300 0.3908 0.3719
0.2261 12.84 1400 0.3850 0.3603
0.1119 13.76 1500 0.3967 0.3645
0.1119 14.68 1600 0.3821 0.3526
0.1119 15.6 1700 0.3919 0.3519
0.1119 16.51 1800 0.3763 0.3366
0.1119 17.43 1900 0.3682 0.3349
0.074 18.35 2000 0.3753 0.3323
0.074 19.27 2100 0.3753 0.3267

Framework versions

  • Transformers 4.28.1
  • Pytorch 1.12.1+cu102
  • Datasets 2.12.0
  • Tokenizers 0.13.3
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Dataset used to train Robinjmf/wav2vec2-common_voice-tr-output

Evaluation results