---
license: apache-2.0
base_model: google-bert/bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-multilingual-uncased-finetuned-ner-geocorpus
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-base-multilingual-uncased-finetuned-ner-geocorpus

This model is a fine-tuned version of [google-bert/bert-base-multilingual-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1337
- Precision: 0.7867
- Recall: 0.8827
- F1: 0.8320
- Accuracy: 0.9727

## 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  | 0.1785          | 0.6910    | 0.6597 | 0.6750 | 0.9527   |
| 0.2507        | 2.0   | 552  | 0.1321          | 0.7761    | 0.7689 | 0.7725 | 0.9630   |
| 0.2507        | 3.0   | 828  | 0.1158          | 0.7691    | 0.8165 | 0.7921 | 0.9669   |
| 0.084         | 4.0   | 1104 | 0.1186          | 0.7503    | 0.8479 | 0.7961 | 0.9668   |
| 0.084         | 5.0   | 1380 | 0.1287          | 0.7629    | 0.8560 | 0.8068 | 0.9657   |
| 0.0443        | 6.0   | 1656 | 0.1295          | 0.7453    | 0.8769 | 0.8058 | 0.9666   |
| 0.0443        | 7.0   | 1932 | 0.1423          | 0.7592    | 0.8862 | 0.8178 | 0.9685   |
| 0.0243        | 8.0   | 2208 | 0.1267          | 0.7970    | 0.8664 | 0.8303 | 0.9724   |
| 0.0243        | 9.0   | 2484 | 0.1309          | 0.7747    | 0.8746 | 0.8216 | 0.9710   |
| 0.0164        | 10.0  | 2760 | 0.1337          | 0.7867    | 0.8827 | 0.8320 | 0.9727   |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1