wolbanking77-afro-xlmr-large

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wolbanking77-afro-xlmr-large

This model is a fine-tuned version of Davlan/afro-xlmr-large on the WolBanking77 dataset. It achieves the following results on the evaluation set:

• Loss: 2.2959
• F1: 0.5810

Model description

See WolBanking77: Wolof Banking Speech Intent Classification Dataset paper

Intended uses & limitations

• Customer Intent Detection
• Machine Translation in French & Wolof
• Automatic Speech Recognition in Wolof
• Comparing different machine learning models for Intent Classification

Training and evaluation data

See WolBanking77 dataset.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 4
• eval_batch_size: 8
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 20

Training results

Framework versions

• Transformers 4.57.1
• Pytorch 2.8.0+cu128
• Datasets 4.2.0
• Tokenizers 0.22.1