---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
datasets:
- id_nergrit_corpus
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-panx-Indo
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: id_nergrit_corpus
      type: id_nergrit_corpus
      config: ner
      split: validation
      args: ner
    metrics:
    - name: F1
      type: f1
      value: 0.83694517516389
---

<!-- 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-Indo

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the id_nergrit_corpus dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1919
- F1: 0.8369

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.3999        | 1.0   | 523  | 0.2013          | 0.8147 |
| 0.1624        | 2.0   | 1046 | 0.1942          | 0.8249 |
| 0.1097        | 3.0   | 1569 | 0.1919          | 0.8369 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1