metadata
language:
- mn
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-multilingual-cased-ner-demo
results: []
bert-multilingual-cased-ner-demo
This model is a fine-tuned version of bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1471
- Precision: 0.9148
- Recall: 0.9229
- F1: 0.9188
- Accuracy: 0.9759
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: 32
- 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 |
|---|---|---|---|---|---|---|---|
| 0.1743 | 1.0 | 477 | 0.0992 | 0.8649 | 0.8914 | 0.8780 | 0.9695 |
| 0.0848 | 2.0 | 954 | 0.0900 | 0.8822 | 0.9010 | 0.8915 | 0.9719 |
| 0.0557 | 3.0 | 1431 | 0.1110 | 0.8848 | 0.9001 | 0.8924 | 0.9699 |
| 0.0411 | 4.0 | 1908 | 0.1061 | 0.8993 | 0.9140 | 0.9066 | 0.9744 |
| 0.0298 | 5.0 | 2385 | 0.1130 | 0.8923 | 0.9147 | 0.9034 | 0.9732 |
| 0.0207 | 6.0 | 2862 | 0.1197 | 0.9078 | 0.9176 | 0.9127 | 0.9756 |
| 0.0144 | 7.0 | 3339 | 0.1372 | 0.9053 | 0.9180 | 0.9116 | 0.9742 |
| 0.0088 | 8.0 | 3816 | 0.1401 | 0.9080 | 0.9195 | 0.9137 | 0.9746 |
| 0.0066 | 9.0 | 4293 | 0.1442 | 0.9100 | 0.9216 | 0.9158 | 0.9753 |
| 0.0054 | 10.0 | 4770 | 0.1471 | 0.9148 | 0.9229 | 0.9188 | 0.9759 |
Framework versions
- Transformers 4.35.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1