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wav2vec2-xls-r-300m-ar

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

  • eval_loss: 3.0191
  • eval_wer: 1.0
  • eval_runtime: 252.2389
  • eval_samples_per_second: 30.217
  • eval_steps_per_second: 0.476
  • epoch: 1.0
  • step: 340

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: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 2000
  • num_epochs: 5
  • mixed_precision_training: Native AMP

Framework versions

  • Transformers 4.17.0.dev0
  • Pytorch 1.10.2+cu102
  • Datasets 1.18.2.dev0
  • Tokenizers 0.11.0

Evaluation Commands

Please use the evaluation script eval.py included in the repo.

  1. To evaluate on speech-recognition-community-v2/dev_data
python eval.py --model_id nouamanetazi/wav2vec2-xls-r-300m-ar --dataset speech-recognition-community-v2/dev_data --config ar --split validation --chunk_length_s 5.0 --stride_length_s 1.0
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Dataset used to train nouamanetazi/wav2vec2-xls-r-300m-ar

Evaluation results