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--- |
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license: apache-2.0 |
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base_model: om-ashish-soni/pos-ner-tagging-v2 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- conll2003 |
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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: pos-ner-tagging-v2 |
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results: |
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- task: |
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name: Token Classification |
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type: token-classification |
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dataset: |
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name: conll2003 |
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type: conll2003 |
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config: conll2003 |
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split: validation |
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args: conll2003 |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.9393653920267203 |
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- name: Recall |
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type: recall |
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value: 0.9408358887483113 |
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- name: F1 |
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type: f1 |
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value: 0.9401000653531749 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9270324365691411 |
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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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# pos-ner-tagging-v2 |
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This model is a fine-tuned version of [om-ashish-soni/pos-ner-tagging-v2](https://huggingface.co/om-ashish-soni/pos-ner-tagging-v2) on the conll2003 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6442 |
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- Precision: 0.9394 |
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- Recall: 0.9408 |
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- F1: 0.9401 |
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- Accuracy: 0.9270 |
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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: 16 |
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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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| 0.3297 | 1.0 | 1756 | 0.4190 | 0.9189 | 0.9231 | 0.9210 | 0.9051 | |
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| 0.2521 | 2.0 | 3512 | 0.3836 | 0.9210 | 0.9300 | 0.9255 | 0.9114 | |
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| 0.1932 | 3.0 | 5268 | 0.4155 | 0.9295 | 0.9338 | 0.9316 | 0.9183 | |
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| 0.1325 | 4.0 | 7024 | 0.3969 | 0.9328 | 0.9356 | 0.9342 | 0.9211 | |
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| 0.0973 | 5.0 | 8780 | 0.4247 | 0.9332 | 0.9367 | 0.9349 | 0.9222 | |
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| 0.0799 | 6.0 | 10536 | 0.4606 | 0.9338 | 0.9374 | 0.9356 | 0.9229 | |
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| 0.0554 | 7.0 | 12292 | 0.4836 | 0.9333 | 0.9379 | 0.9356 | 0.9239 | |
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| 0.0415 | 8.0 | 14048 | 0.5271 | 0.9361 | 0.9391 | 0.9376 | 0.9245 | |
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| 0.0285 | 9.0 | 15804 | 0.5363 | 0.9366 | 0.9397 | 0.9381 | 0.9253 | |
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| 0.022 | 10.0 | 17560 | 0.5653 | 0.9377 | 0.9396 | 0.9387 | 0.9258 | |
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| 0.0146 | 11.0 | 19316 | 0.5962 | 0.9374 | 0.9400 | 0.9387 | 0.9259 | |
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| 0.0121 | 12.0 | 21072 | 0.6061 | 0.9385 | 0.9401 | 0.9393 | 0.9266 | |
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| 0.0085 | 13.0 | 22828 | 0.6263 | 0.9384 | 0.9403 | 0.9394 | 0.9261 | |
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| 0.0062 | 14.0 | 24584 | 0.6365 | 0.9381 | 0.9399 | 0.9390 | 0.9259 | |
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| 0.0053 | 15.0 | 26340 | 0.6386 | 0.9384 | 0.9402 | 0.9393 | 0.9264 | |
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| 0.0042 | 16.0 | 28096 | 0.6442 | 0.9394 | 0.9408 | 0.9401 | 0.9270 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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