metadata
base_model: NlpHUST/ner-vietnamese-electra-base
tags:
- generated_from_trainer
model-index:
- name: ner-education-hcmut
results: []
ner-education-hcmut
This model is a fine-tuned version of NlpHUST/ner-vietnamese-electra-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0681
- Location: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 7}
- Miscellaneous: {'precision': 0.6911764705882353, 'recall': 0.7230769230769231, 'f1': 0.7067669172932332, 'number': 65}
- Organization: {'precision': 0.4166666666666667, 'recall': 0.5, 'f1': 0.45454545454545453, 'number': 10}
- Person: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3}
- Overall Precision: 0.6190
- Overall Recall: 0.6118
- Overall F1: 0.6154
- Overall Accuracy: 0.9851
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Location | Miscellaneous | Organization | Person | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|---|---|---|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 207 | 0.0705 | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 7} | {'precision': 0.49333333333333335, 'recall': 0.5692307692307692, 'f1': 0.5285714285714285, 'number': 65} | {'precision': 0.36363636363636365, 'recall': 0.4, 'f1': 0.380952380952381, 'number': 10} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3} | 0.4556 | 0.4824 | 0.4686 | 0.9806 |
| No log | 2.0 | 414 | 0.0672 | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 7} | {'precision': 0.6133333333333333, 'recall': 0.7076923076923077, 'f1': 0.657142857142857, 'number': 65} | {'precision': 0.4666666666666667, 'recall': 0.7, 'f1': 0.56, 'number': 10} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3} | 0.5638 | 0.6235 | 0.5922 | 0.9838 |
| 0.0564 | 3.0 | 621 | 0.0681 | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 7} | {'precision': 0.6911764705882353, 'recall': 0.7230769230769231, 'f1': 0.7067669172932332, 'number': 65} | {'precision': 0.4166666666666667, 'recall': 0.5, 'f1': 0.45454545454545453, 'number': 10} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3} | 0.6190 | 0.6118 | 0.6154 | 0.9851 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1