README.md

metadata

language:
  - ar
license: apache-2.0
tags:
  - ar
  - automatic-speech-recognition
  - common_voice
  - generated_from_trainer
  - hf-asr-leaderboard
  - robust-speech-event
datasets:
  - common_voice
model-index:
  - name: XLS-R-300M - Arabic
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Robust Speech Event - Dev Data
          type: speech-recognition-community-v2/dev_data
          args: ar
        metrics:
          - name: Test WER
            type: wer
            value: 1
          - name: Test CER
            type: cer
            value: 1

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