Edit model card

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
Downloads last month
40
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Dataset used to train nouamanetazi/wav2vec2-xls-r-300m-ar-with-lm

Evaluation results