---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: xlm-roberta-base-finetuned-ner-geocorpus
  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-base-finetuned-ner-geocorpus

This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1081
- Precision: 0.8117
- Recall: 0.8791
- F1: 0.8440
- Accuracy: 0.9765

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 276  | 0.2364          | 0.5253    | 0.4795 | 0.5014 | 0.9411   |
| 0.3373        | 2.0   | 552  | 0.1581          | 0.7023    | 0.7592 | 0.7297 | 0.9616   |
| 0.3373        | 3.0   | 828  | 0.1280          | 0.8232    | 0.7245 | 0.7707 | 0.9672   |
| 0.1133        | 4.0   | 1104 | 0.1229          | 0.7239    | 0.8601 | 0.7862 | 0.9667   |
| 0.1133        | 5.0   | 1380 | 0.1100          | 0.7764    | 0.8801 | 0.8250 | 0.9722   |
| 0.0635        | 6.0   | 1656 | 0.0978          | 0.8065    | 0.8896 | 0.846  | 0.9772   |
| 0.0635        | 7.0   | 1932 | 0.0942          | 0.8189    | 0.8749 | 0.8460 | 0.9774   |
| 0.0416        | 8.0   | 2208 | 0.1083          | 0.8097    | 0.8591 | 0.8337 | 0.9756   |
| 0.0416        | 9.0   | 2484 | 0.1062          | 0.8027    | 0.8896 | 0.8439 | 0.9767   |
| 0.0292        | 10.0  | 2760 | 0.1081          | 0.8117    | 0.8791 | 0.8440 | 0.9765   |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1