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-wol
    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: 0.7235926628716003

xlm-roberta-base-finetuned-wol

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: 0.0815
• F1: 0.7236

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: 64
• eval_batch_size: 64
• 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
No log	1.0	72	0.1272	0.5887
0.2412	2.0	144	0.0916	0.6888
0.2412	3.0	216	0.0815	0.7236

Framework versions

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