---
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: 0.1210
- Precision: 0.8205
- Recall: 0.8757
- F1: 0.8472
- Accuracy: 0.9760

## 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  | 0.1670          | 0.7138    | 0.6690 | 0.6906 | 0.9555   |
| 0.247         | 2.0   | 552  | 0.1192          | 0.8109    | 0.7770 | 0.7936 | 0.9676   |
| 0.247         | 3.0   | 828  | 0.1181          | 0.8226    | 0.8188 | 0.8207 | 0.9709   |
| 0.0846        | 4.0   | 1104 | 0.1162          | 0.7656    | 0.8571 | 0.8088 | 0.9685   |
| 0.0846        | 5.0   | 1380 | 0.1248          | 0.7627    | 0.8699 | 0.8128 | 0.9687   |
| 0.0442        | 6.0   | 1656 | 0.0982          | 0.8233    | 0.8931 | 0.8568 | 0.9777   |
| 0.0442        | 7.0   | 1932 | 0.1114          | 0.8100    | 0.8862 | 0.8464 | 0.9741   |
| 0.0247        | 8.0   | 2208 | 0.1164          | 0.8342    | 0.8885 | 0.8605 | 0.9780   |
| 0.0247        | 9.0   | 2484 | 0.1208          | 0.7983    | 0.8920 | 0.8426 | 0.9746   |
| 0.0159        | 10.0  | 2760 | 0.1210          | 0.8205    | 0.8757 | 0.8472 | 0.9760   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1