| --- |
| language: |
| - mn |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: testingModel |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # testingModel |
|
|
| This model is a fine-tuned version of [Davlan/distilbert-base-multilingual-cased-ner-hrl](https://huggingface.co/Davlan/distilbert-base-multilingual-cased-ner-hrl) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1368 |
| - Precision: 0.8763 |
| - Recall: 0.9000 |
| - F1: 0.8880 |
| - Accuracy: 0.9738 |
|
|
| ## 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | 0.1975 | 1.0 | 477 | 0.1150 | 0.8257 | 0.8574 | 0.8412 | 0.9642 | |
| | 0.1001 | 2.0 | 954 | 0.1046 | 0.8515 | 0.8798 | 0.8654 | 0.9682 | |
| | 0.0655 | 3.0 | 1431 | 0.0980 | 0.8632 | 0.8905 | 0.8766 | 0.9719 | |
| | 0.0453 | 4.0 | 1908 | 0.1088 | 0.8590 | 0.8944 | 0.8763 | 0.9718 | |
| | 0.0324 | 5.0 | 2385 | 0.1142 | 0.8673 | 0.8951 | 0.8810 | 0.9719 | |
| | 0.0223 | 6.0 | 2862 | 0.1244 | 0.8814 | 0.9036 | 0.8924 | 0.9737 | |
| | 0.0173 | 7.0 | 3339 | 0.1252 | 0.8739 | 0.9007 | 0.8871 | 0.9733 | |
| | 0.0131 | 8.0 | 3816 | 0.1328 | 0.8721 | 0.8965 | 0.8841 | 0.9731 | |
| | 0.0097 | 9.0 | 4293 | 0.1362 | 0.8783 | 0.9002 | 0.8891 | 0.9737 | |
| | 0.008 | 10.0 | 4770 | 0.1368 | 0.8763 | 0.9000 | 0.8880 | 0.9738 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.28.0 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.12.0 |
| - Tokenizers 0.13.3 |
|
|
