README.md

metadata

license: mit
base_model: xlm-roberta-large
tags:
  - generated_from_trainer
datasets:
  - masakhaner2
metrics:
  - f1
model-index:
  - name: xlm-roberta-large-finetuned-wolof
    results:
      - task:
          name: Token Classification
          type: token-classification
        dataset:
          name: masakhaner2
          type: masakhaner2
          config: wol
          split: validation
          args: wol
        metrics:
          - name: F1
            type: f1
            value: 0.8378048780487805

xlm-roberta-large-finetuned-wolof

This model is a fine-tuned version of xlm-roberta-large on the masakhaner2 dataset. It achieves the following results on the evaluation set:

• Loss: 0.2882
• F1: 0.8378

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: 5e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	F1
0.6633	1.0	739	0.3813	0.7486
0.259	2.0	1478	0.2772	0.7903
0.1289	3.0	2217	0.2882	0.8378

Framework versions

• Transformers 4.33.0
• Pytorch 2.0.0
• Datasets 2.1.0
• Tokenizers 0.13.3