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---
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