metadata
language:
- mn
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: mongolian-gpt2-ner-finetuning
results: []
mongolian-gpt2-ner-finetuning
This model is a fine-tuned version of bayartsogt/mongolian-gpt2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3230
- Precision: 0.0989
- Recall: 0.2277
- F1: 0.1380
- Accuracy: 0.9078
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 |
|---|---|---|---|---|---|---|---|
| 0.5225 | 1.0 | 477 | 0.3650 | 0.0743 | 0.1674 | 0.1030 | 0.8821 |
| 0.322 | 2.0 | 954 | 0.3129 | 0.0853 | 0.1903 | 0.1178 | 0.8966 |
| 0.2681 | 3.0 | 1431 | 0.3008 | 0.0915 | 0.2034 | 0.1262 | 0.9022 |
| 0.232 | 4.0 | 1908 | 0.2963 | 0.0914 | 0.2070 | 0.1269 | 0.9053 |
| 0.2029 | 5.0 | 2385 | 0.2974 | 0.0933 | 0.2120 | 0.1295 | 0.9071 |
| 0.1791 | 6.0 | 2862 | 0.3038 | 0.0949 | 0.2140 | 0.1315 | 0.9076 |
| 0.1603 | 7.0 | 3339 | 0.3100 | 0.0958 | 0.2186 | 0.1332 | 0.9079 |
| 0.146 | 8.0 | 3816 | 0.3174 | 0.0950 | 0.2156 | 0.1319 | 0.9079 |
| 0.1355 | 9.0 | 4293 | 0.3233 | 0.1001 | 0.2274 | 0.1390 | 0.9080 |
| 0.1291 | 10.0 | 4770 | 0.3230 | 0.0989 | 0.2277 | 0.1380 | 0.9078 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3