metadata
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: []
bert-base-multilingual-uncased-finetuned-ner-geocorpus
This model is a fine-tuned version of google-bert/bert-base-multilingual-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1137
- Precision: 0.8040
- Recall: 0.7863
- F1: 0.7951
- Accuracy: 0.9678
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: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 276 | 0.1781 | 0.6711 | 0.6469 | 0.6588 | 0.9541 |
| 0.2543 | 2.0 | 552 | 0.1287 | 0.7567 | 0.7875 | 0.7718 | 0.9638 |
| 0.2543 | 3.0 | 828 | 0.1137 | 0.8040 | 0.7863 | 0.7951 | 0.9678 |
| 0.0868 | 4.0 | 1104 | 0.1205 | 0.7628 | 0.8630 | 0.8098 | 0.9674 |
| 0.0868 | 5.0 | 1380 | 0.1184 | 0.8093 | 0.8722 | 0.8396 | 0.9722 |
| 0.0448 | 6.0 | 1656 | 0.1148 | 0.7817 | 0.8943 | 0.8342 | 0.9723 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1