README.md

metadata

license: mit
base_model: xlm-roberta-base
tags:
  - generated_from_trainer
datasets:
  - masakhaner2
metrics:
  - f1
model-index:
  - name: xlm-roberta-base-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: 0.8217446270543616

xlm-roberta-base-finetuned-wolof

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

• Loss: 0.0589
• F1: 0.8217

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: 24
• eval_batch_size: 24
• 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
0.2113	1.0	247	0.0823	0.7443
0.0749	2.0	494	0.0635	0.8097
0.0445	3.0	741	0.0589	0.8217

Framework versions

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