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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - common_voice
model-index:
  - name: wav2vec2-large-mn-pretrain-42h-100-epochs
    results: []

wav2vec2-large-mn-pretrain-42h-100-epochs

This model is a fine-tuned version of bayartsogt/wav2vec2-large-mn-pretrain-42h on the common_voice dataset. It achieves the following results on the evaluation set:

  • Loss: 6.4172
  • Wer: 1.0
  • Cer: 0.9841

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: 2e-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: 10000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer
7.6418 1.59 400 6.4239 1.0 0.9841
5.5936 3.19 800 6.4154 1.0 0.9841
5.5208 4.78 1200 6.5248 1.0 0.9841
5.4869 6.37 1600 6.3805 1.0 0.9841
5.4757 7.97 2000 6.3988 1.0 0.9841
5.4624 9.56 2400 6.4058 1.0 0.9841
5.517 11.16 2800 6.3991 1.0 0.9841
5.4821 12.75 3200 6.4066 1.0 0.9841
5.487 14.34 3600 6.4281 1.0 0.9841
5.4786 15.93 4000 6.4174 1.0 0.9841
5.5017 17.53 4400 6.4338 1.0 0.9841
5.4967 19.12 4800 6.4653 1.0 0.9841
5.4619 20.72 5200 6.4499 1.0 0.9841
5.4883 22.31 5600 6.4345 1.0 0.9841
5.4899 23.9 6000 6.4224 1.0 0.9841
5.493 25.5 6400 6.4374 1.0 0.9841
5.4549 27.09 6800 6.4320 1.0 0.9841
5.4531 28.68 7200 6.4137 1.0 0.9841
5.4738 30.28 7600 6.4155 1.0 0.9841
5.4309 31.87 8000 6.4193 1.0 0.9841
5.4669 33.47 8400 6.4109 1.0 0.9841
5.47 35.06 8800 6.4111 1.0 0.9841
5.4623 36.65 9200 6.4102 1.0 0.9841
5.4583 38.25 9600 6.4150 1.0 0.9841
5.4551 39.84 10000 6.4172 1.0 0.9841

Framework versions

  • Transformers 4.20.1
  • Pytorch 1.11.0
  • Datasets 2.1.0
  • Tokenizers 0.12.1