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metadata
language:
  - tr
license: apache-2.0
tags:
  - automatic-speech-recognition
  - common_voice
  - generated_from_trainer
model-index:
  - name: wav2vec2-xls-r-common_voice-tr-ft-500sh
    results: []

wav2vec2-xls-r-common_voice-tr-ft-500sh

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: 0.5794
  • Wer: 0.4009
  • Cer: 0.1032

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: 4
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • total_eval_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: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer
0.5288 17.0 500 0.5099 0.5426 0.1432
0.2967 34.0 1000 0.5421 0.4746 0.1256
0.2447 51.0 1500 0.5347 0.4831 0.1267
0.122 68.01 2000 0.5854 0.4479 0.1161
0.1035 86.0 2500 0.5597 0.4457 0.1166
0.081 103.0 3000 0.5748 0.4250 0.1144
0.0849 120.0 3500 0.5598 0.4337 0.1145
0.0542 137.01 4000 0.5687 0.4223 0.1097
0.0318 155.0 4500 0.5904 0.4057 0.1052
0.0106 172.0 5000 0.5794 0.4009 0.1032

Framework versions

  • Transformers 4.17.0.dev0
  • Pytorch 1.10.2
  • Datasets 1.18.2
  • Tokenizers 0.10.3