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---
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language:
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- mn
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license: mit
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: mongolian-gpt2-ner
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# mongolian-gpt2-ner
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This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2599
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- Precision: 0.1483
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- Recall: 0.2561
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- F1: 0.1878
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- Accuracy: 0.9149
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 32
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 0.4822 | 1.0 | 477 | 0.3452 | 0.1156 | 0.2072 | 0.1484 | 0.8876 |
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| 0.3376 | 2.0 | 954 | 0.3196 | 0.1369 | 0.2304 | 0.1717 | 0.8975 |
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| 0.3084 | 3.0 | 1431 | 0.2915 | 0.1242 | 0.2257 | 0.1603 | 0.9015 |
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| 0.2889 | 4.0 | 1908 | 0.2800 | 0.1328 | 0.2375 | 0.1704 | 0.9063 |
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| 0.275 | 5.0 | 2385 | 0.2734 | 0.1439 | 0.2452 | 0.1814 | 0.9099 |
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| 0.264 | 6.0 | 2862 | 0.2691 | 0.1426 | 0.2420 | 0.1795 | 0.9115 |
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| 0.256 | 7.0 | 3339 | 0.2639 | 0.1411 | 0.2442 | 0.1789 | 0.9129 |
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| 0.2498 | 8.0 | 3816 | 0.2628 | 0.1482 | 0.2511 | 0.1864 | 0.9135 |
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| 0.2438 | 9.0 | 4293 | 0.2603 | 0.1483 | 0.2548 | 0.1875 | 0.9143 |
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| 0.2388 | 10.0 | 4770 | 0.2599 | 0.1483 | 0.2561 | 0.1878 | 0.9149 |
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### Framework versions
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- Transformers 4.29.2
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- Pytorch 2.0.1+cu118
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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