README.md

metadata

license: mit
base_model: xlm-roberta-base
tags:
  - generated_from_trainer
datasets:
  - xtreme
metrics:
  - f1
model-index:
  - name: xlm-roberta-base-finetuned-panx-en
    results:
      - task:
          name: Token Classification
          type: token-classification
        dataset:
          name: xtreme
          type: xtreme
          config: PAN-X.en
          split: validation
          args: PAN-X.en
        metrics:
          - name: F1
            type: f1
            value: 0.6856504745951982

xlm-roberta-base-finetuned-panx-en

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

• Loss: 0.3963
• F1: 0.6857

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
1.1492	1.0	50	0.5984	0.5425
0.5072	2.0	100	0.4348	0.6530
0.3796	3.0	150	0.3963	0.6857

Framework versions

• Transformers 4.31.0
• Pytorch 2.1.0.dev20230810
• Datasets 2.14.3
• Tokenizers 0.13.3