transformers pytorch tensorboard xlm-roberta token-classification generated_from_trainer dataset:xtreme license:mit model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- xtreme
license: mit
metrics:
- f1
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base-finetuned-panx-de
  results:
  - task:
      type: token-classification
      name: Token Classification
    dataset:
      name: xtreme
      type: xtreme
      args: PAN-X.de
    metrics:
    - type: f1
      value: 0.8645910410381922
      name: F1
---

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# xlm-roberta-base-finetuned-panx-de

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the PAN-X dataset. The model is trained in Chapter 4: Multilingual Named Entity Recognition in the [NLP with Transformers book](https://learning.oreilly.com/library/view/natural-language-processing/9781098103231/). You can find the full code in the accompanying [Github repository](https://github.com/nlp-with-transformers/notebooks/blob/main/04_multilingual-ner.ipynb).

It achieves the following results on the evaluation set:
- Loss: 0.1388
- F1: 0.8646

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.2652        | 1.0   | 525  | 0.1602          | 0.8230 |
| 0.1314        | 2.0   | 1050 | 0.1372          | 0.8527 |
| 0.0806        | 3.0   | 1575 | 0.1388          | 0.8646 |


### Framework versions

- Transformers 4.12.0.dev0
- Pytorch 1.9.1+cu102
- Datasets 1.12.1
- Tokenizers 0.10.3
