metadata
language:
- mn
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: mongolian-roberta-base
results: []
mongolian-roberta-base
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: 0.1308
- Precision: 0.9243
- Recall: 0.9322
- F1: 0.9283
- Accuracy: 0.9799
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: 9
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1632 | 1.0 | 477 | 0.0908 | 0.8293 | 0.8817 | 0.8547 | 0.9682 |
| 0.0607 | 2.0 | 954 | 0.0920 | 0.8506 | 0.8898 | 0.8698 | 0.9712 |
| 0.0331 | 3.0 | 1431 | 0.0975 | 0.9192 | 0.9267 | 0.9229 | 0.9779 |
| 0.0148 | 4.0 | 1908 | 0.1024 | 0.9179 | 0.9294 | 0.9236 | 0.9786 |
| 0.0087 | 5.0 | 2385 | 0.1091 | 0.9196 | 0.9296 | 0.9246 | 0.9796 |
| 0.0052 | 6.0 | 2862 | 0.1222 | 0.9240 | 0.9323 | 0.9281 | 0.9794 |
| 0.0033 | 7.0 | 3339 | 0.1233 | 0.9214 | 0.9317 | 0.9265 | 0.9796 |
| 0.0024 | 8.0 | 3816 | 0.1310 | 0.9250 | 0.9315 | 0.9282 | 0.9797 |
| 0.0016 | 9.0 | 4293 | 0.1308 | 0.9243 | 0.9322 | 0.9283 | 0.9799 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3