---
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-large-finetuned-ner-vlsp2021-3090-1July-1
  results: []
---

<!-- 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-large-finetuned-ner-vlsp2021-3090-1July-1

This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.1332
- eval_ATETIME: {'precision': 0.8748768472906404, 'recall': 0.8862275449101796, 'f1': 0.8805156172533465, 'number': 1002}
- eval_DDRESS: {'precision': 0.7837837837837838, 'recall': 1.0, 'f1': 0.8787878787878788, 'number': 29}
- eval_ERSON: {'precision': 0.9496365524402908, 'recall': 0.9631384939441812, 'f1': 0.9563398692810458, 'number': 1899}
- eval_ERSONTYPE: {'precision': 0.7142857142857143, 'recall': 0.7602339181286549, 'f1': 0.7365439093484419, 'number': 684}
- eval_HONENUMBER: {'precision': 1.0, 'recall': 0.8888888888888888, 'f1': 0.9411764705882353, 'number': 9}
- eval_ISCELLANEOUS: {'precision': 0.5521472392638037, 'recall': 0.5660377358490566, 'f1': 0.5590062111801242, 'number': 159}
- eval_MAIL: {'precision': 1.0, 'recall': 0.9803921568627451, 'f1': 0.99009900990099, 'number': 51}
- eval_OCATION: {'precision': 0.8478731074260994, 'recall': 0.9039200614911607, 'f1': 0.875, 'number': 1301}
- eval_P: {'precision': 0.9090909090909091, 'recall': 0.9090909090909091, 'f1': 0.9090909090909091, 'number': 11}
- eval_RL: {'precision': 0.5789473684210527, 'recall': 0.7333333333333333, 'f1': 0.6470588235294117, 'number': 15}
- eval_RODUCT: {'precision': 0.7018739352640545, 'recall': 0.6592, 'f1': 0.6798679867986799, 'number': 625}
- eval_overall_precision: 0.8469
- eval_overall_recall: 0.8683
- eval_overall_f1: 0.8575
- eval_overall_accuracy: 0.9793
- eval_runtime: 38.9411
- eval_samples_per_second: 64.919
- eval_steps_per_second: 16.23
- epoch: 7.0
- step: 22841

## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Framework versions

- Transformers 4.40.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1