metadata
language:
- mn
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: roberta-base-ner-demo
results: []
roberta-base-ner-demo
This model is a fine-tuned version of bayartsogt/mongolian-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1349
- Precision: 0.9210
- Recall: 0.9330
- F1: 0.9269
- Accuracy: 0.9788
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 |
|---|---|---|---|---|---|---|---|
| 0.1615 | 1.0 | 477 | 0.0917 | 0.8327 | 0.8817 | 0.8565 | 0.9680 |
| 0.0615 | 2.0 | 954 | 0.0917 | 0.8432 | 0.8918 | 0.8668 | 0.9701 |
| 0.0404 | 3.0 | 1431 | 0.0961 | 0.8411 | 0.8970 | 0.8682 | 0.9710 |
| 0.0227 | 4.0 | 1908 | 0.1056 | 0.9081 | 0.9262 | 0.9171 | 0.9770 |
| 0.0133 | 5.0 | 2385 | 0.1117 | 0.8781 | 0.9108 | 0.8942 | 0.9744 |
| 0.0083 | 6.0 | 2862 | 0.1231 | 0.9111 | 0.9288 | 0.9199 | 0.9775 |
| 0.0061 | 7.0 | 3339 | 0.1263 | 0.9110 | 0.9293 | 0.9200 | 0.9776 |
| 0.0071 | 8.0 | 3816 | 0.1316 | 0.9197 | 0.9302 | 0.9249 | 0.9783 |
| 0.0031 | 9.0 | 4293 | 0.1335 | 0.9228 | 0.9327 | 0.9277 | 0.9790 |
| 0.0021 | 10.0 | 4770 | 0.1349 | 0.9210 | 0.9330 | 0.9269 | 0.9788 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3