---
license: mit
base_model: xlm-roberta-base
tags:
- pytorch
- XLMRobertaForTokenClassification
- named-entity-recognition
- wikipedia
- generated_from_trainer
model-index:
- name: xlm-roberta-base-wikineural
  results: []
datasets:
- tner/wikineural
- tner/multinerd
library_name: transformers
pipeline_tag: token-classification
---

<!-- 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-wikineural

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0467

## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 128
- seed: 37912547
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 100000

### Training results

| Training Loss | Epoch | Step   | Validation Loss |
|:-------------:|:-----:|:------:|:---------------:|
| 0.0858        | 0.14  | 10000  | 0.0817          |
| 0.0719        | 0.28  | 20000  | 0.0660          |
| 0.0656        | 0.43  | 30000  | 0.0631          |
| 0.0598        | 0.57  | 40000  | 0.0574          |
| 0.0551        | 0.71  | 50000  | 0.0534          |
| 0.0523        | 0.85  | 60000  | 0.0512          |
| 0.0519        | 0.99  | 70000  | 0.0484          |
| 0.0418        | 1.13  | 80000  | 0.0480          |
| 0.042         | 1.28  | 90000  | 0.0469          |
| 0.041         | 1.42  | 100000 | 0.0467          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0