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--- |
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language: |
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- mn |
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license: apache-2.0 |
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base_model: bert-base-multilingual-cased |
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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: bert-multilingual-cased-ner-demo |
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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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# bert-multilingual-cased-ner-demo |
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This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1471 |
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- Precision: 0.9148 |
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- Recall: 0.9229 |
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- F1: 0.9188 |
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- Accuracy: 0.9759 |
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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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| 0.1743 | 1.0 | 477 | 0.0992 | 0.8649 | 0.8914 | 0.8780 | 0.9695 | |
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| 0.0848 | 2.0 | 954 | 0.0900 | 0.8822 | 0.9010 | 0.8915 | 0.9719 | |
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| 0.0557 | 3.0 | 1431 | 0.1110 | 0.8848 | 0.9001 | 0.8924 | 0.9699 | |
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| 0.0411 | 4.0 | 1908 | 0.1061 | 0.8993 | 0.9140 | 0.9066 | 0.9744 | |
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| 0.0298 | 5.0 | 2385 | 0.1130 | 0.8923 | 0.9147 | 0.9034 | 0.9732 | |
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| 0.0207 | 6.0 | 2862 | 0.1197 | 0.9078 | 0.9176 | 0.9127 | 0.9756 | |
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| 0.0144 | 7.0 | 3339 | 0.1372 | 0.9053 | 0.9180 | 0.9116 | 0.9742 | |
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| 0.0088 | 8.0 | 3816 | 0.1401 | 0.9080 | 0.9195 | 0.9137 | 0.9746 | |
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| 0.0066 | 9.0 | 4293 | 0.1442 | 0.9100 | 0.9216 | 0.9158 | 0.9753 | |
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| 0.0054 | 10.0 | 4770 | 0.1471 | 0.9148 | 0.9229 | 0.9188 | 0.9759 | |
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### Framework versions |
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- Transformers 4.35.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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