metadata
language:
- mn
base_model: bayartsogt/mongolian-roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: roberta-base-ner-test-2
results: []
roberta-base-ner-test-2
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: 0.0742
- Precision: 0.8999
- Recall: 0.9142
- F1: 0.9070
- Accuracy: 0.9776
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: 128
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.4131 | 1.0 | 60 | 0.1140 | 0.8104 | 0.8399 | 0.8249 | 0.9630 |
| 0.0936 | 2.0 | 120 | 0.0785 | 0.8835 | 0.9020 | 0.8926 | 0.9748 |
| 0.0617 | 3.0 | 180 | 0.0742 | 0.8999 | 0.9142 | 0.9070 | 0.9776 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2