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wav2vec2-large-mn-pretrain-42h-finetuned

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:

  • eval_loss: 3.2032
  • eval_wer: 1.0
  • eval_cer: 1.0
  • eval_runtime: 229.9508
  • eval_samples_per_second: 8.202
  • eval_steps_per_second: 1.026
  • epoch: 25.4
  • step: 3200

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: 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
  • training_steps: 10000
  • mixed_precision_training: Native AMP

Framework versions

  • Transformers 4.20.1
  • Pytorch 1.11.0
  • Datasets 2.1.0
  • Tokenizers 0.12.1
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Dataset used to train bayartsogt/wav2vec2-large-mn-pretrain-42h-finetuned