metadata

license: mit
tags:
  - generated_from_trainer
datasets:
  - xtreme
metrics:
  - f1
model-index:
  - name: xlm-roberta-base-finetuned-panx-de
    results:
      - task:
          name: Token Classification
          type: token-classification
        dataset:
          name: xtreme
          type: xtreme
          config: PAN-X.de
          split: validation
          args: PAN-X.de
        metrics:
          - name: F1
            type: f1
            value: 0.8580992907801419

xlm-roberta-base-finetuned-panx-de

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: 0.1368
F1: 0.8581

Model description

More information needed

Intended uses & limitations

This is a simple test from the O'Reilly's book "Natural Language Processing with Transformers". Not to use for anything but testing purposes.

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
0.256	1.0	525	0.1580	0.8335
0.13	2.0	1050	0.1368	0.8519
0.082	3.0	1575	0.1368	0.8581

Framework versions

Transformers 4.28.1
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.13.3