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---
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
should probably proofread and complete it, then remove this comment. -->
# 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
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