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---
license: mit
tags:
- generated_from_trainer
datasets:
- xtreme
metrics:
- f1
base_model: xlm-roberta-base
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: 0.8633929588697733
name: F1
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 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 xtreme dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1366
- F1: 0.8634
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.2587 | 1.0 | 525 | 0.1542 | 0.8213 |
| 0.1302 | 2.0 | 1050 | 0.1373 | 0.8546 |
| 0.0827 | 3.0 | 1575 | 0.1366 | 0.8634 |
### Framework versions
- Transformers 4.11.3
- Pytorch 1.13.1+cu117
- Datasets 2.9.0
- Tokenizers 0.10.3
|