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--- |
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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: urdu-bert-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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# urdu-bert-ner |
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This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2125 |
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- Precision: 0.8073 |
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- Recall: 0.8272 |
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- F1: 0.8171 |
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- Accuracy: 0.9592 |
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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: 8 |
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- eval_batch_size: 8 |
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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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| 0.1593 | 1.0 | 2272 | 0.1469 | 0.7158 | 0.8005 | 0.7558 | 0.9468 | |
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| 0.1154 | 2.0 | 4544 | 0.1304 | 0.7720 | 0.8116 | 0.7913 | 0.9547 | |
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| 0.0862 | 3.0 | 6816 | 0.1381 | 0.7912 | 0.8117 | 0.8013 | 0.9557 | |
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| 0.0673 | 4.0 | 9088 | 0.1404 | 0.8006 | 0.8099 | 0.8052 | 0.9567 | |
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| 0.0515 | 5.0 | 11360 | 0.1511 | 0.8135 | 0.8063 | 0.8099 | 0.9578 | |
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| 0.0402 | 6.0 | 13632 | 0.1666 | 0.8030 | 0.8235 | 0.8131 | 0.9582 | |
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| 0.0286 | 7.0 | 15904 | 0.1848 | 0.8066 | 0.8208 | 0.8137 | 0.9579 | |
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| 0.022 | 8.0 | 18176 | 0.1957 | 0.8060 | 0.8226 | 0.8142 | 0.9585 | |
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| 0.0201 | 9.0 | 20448 | 0.2062 | 0.8022 | 0.8283 | 0.8151 | 0.9585 | |
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| 0.0164 | 10.0 | 22720 | 0.2125 | 0.8073 | 0.8272 | 0.8171 | 0.9592 | |
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### Framework versions |
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- Transformers 4.33.0 |
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- Pytorch 2.0.0 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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