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: 0.8361858190709046

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: 0.3771
• F1: 0.8362

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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	F1
0.7475	1.0	739	0.4053	0.6989
0.3252	2.0	1478	0.3251	0.6653
0.1983	3.0	2217	0.3703	0.8234
0.1139	4.0	2956	0.3170	0.8299
0.052	5.0	3695	0.3771	0.8362

Framework versions

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