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metadata
language:
  - tr
license: apache-2.0
tags:
  - automatic-speech-recognition
  - common_voice
  - generated_from_trainer
datasets:
  - common_voice
model-index:
  - name: wav2vec2-large-xls-r-300m-common_voice-tr-ft
    results: []

wav2vec2-large-xls-r-300m-common_voice-tr-ft

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the COMMON_VOICE - TR dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3823
  • Wer: 0.3209
  • Cer: 0.0771

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: 0.0005
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • total_train_batch_size: 64
  • total_eval_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 75.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer
0.7638 9.09 500 0.4763 0.5313 0.1333
0.5739 18.18 1000 0.4007 0.4357 0.1099
0.4343 27.27 1500 0.3819 0.4060 0.1012
0.4401 36.36 2000 0.3991 0.3954 0.1001
0.2647 45.45 2500 0.3901 0.3689 0.0914
0.2656 54.55 3000 0.3866 0.3463 0.0852
0.2586 63.64 3500 0.3779 0.3297 0.0804
0.2041 72.73 4000 0.3854 0.3234 0.0776

Framework versions

  • Transformers 4.13.0.dev0
  • Pytorch 1.9.0+cu111
  • Datasets 1.15.2.dev0
  • Tokenizers 0.10.3