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--- |
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license: apache-2.0 |
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base_model: bert-base-cased |
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tags: |
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- generated_from_trainer |
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datasets: |
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- conll2002 |
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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-finetuned-ner-cfv |
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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: conll2002 |
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type: conll2002 |
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config: es |
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split: validation |
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args: es |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.807683615819209 |
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- name: Recall |
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type: recall |
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value: 0.8212316176470589 |
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- name: F1 |
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type: f1 |
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value: 0.8144012760624361 |
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- name: Accuracy |
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type: accuracy |
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value: 0.974075543714453 |
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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-finetuned-ner-cfv |
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This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the conll2002 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1851 |
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- Precision: 0.8077 |
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- Recall: 0.8212 |
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- F1: 0.8144 |
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- Accuracy: 0.9741 |
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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: 4e-05 |
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- train_batch_size: 24 |
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- eval_batch_size: 24 |
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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: 17 |
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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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| No log | 1.0 | 347 | 0.1278 | 0.7284 | 0.7475 | 0.7378 | 0.9646 | |
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| 0.1176 | 2.0 | 694 | 0.1212 | 0.7509 | 0.7806 | 0.7654 | 0.9681 | |
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| 0.0453 | 3.0 | 1041 | 0.1156 | 0.8062 | 0.8116 | 0.8089 | 0.9730 | |
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| 0.0453 | 4.0 | 1388 | 0.1270 | 0.8081 | 0.8031 | 0.8056 | 0.9720 | |
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| 0.0233 | 5.0 | 1735 | 0.1298 | 0.8145 | 0.8231 | 0.8187 | 0.9746 | |
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| 0.0145 | 6.0 | 2082 | 0.1431 | 0.7950 | 0.8091 | 0.8020 | 0.9728 | |
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| 0.0145 | 7.0 | 2429 | 0.1501 | 0.8103 | 0.8166 | 0.8135 | 0.9734 | |
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| 0.009 | 8.0 | 2776 | 0.1553 | 0.8118 | 0.8157 | 0.8138 | 0.9738 | |
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| 0.0061 | 9.0 | 3123 | 0.1572 | 0.7891 | 0.8084 | 0.7986 | 0.9720 | |
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| 0.0061 | 10.0 | 3470 | 0.1589 | 0.8142 | 0.8196 | 0.8169 | 0.9739 | |
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| 0.005 | 11.0 | 3817 | 0.1671 | 0.8092 | 0.8148 | 0.8120 | 0.9733 | |
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| 0.0032 | 12.0 | 4164 | 0.1716 | 0.8066 | 0.8139 | 0.8102 | 0.9733 | |
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| 0.0031 | 13.0 | 4511 | 0.1767 | 0.8025 | 0.8169 | 0.8096 | 0.9731 | |
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| 0.0031 | 14.0 | 4858 | 0.1756 | 0.8096 | 0.8217 | 0.8156 | 0.9741 | |
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| 0.0023 | 15.0 | 5205 | 0.1845 | 0.8109 | 0.8157 | 0.8133 | 0.9739 | |
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| 0.0018 | 16.0 | 5552 | 0.1850 | 0.8090 | 0.8203 | 0.8146 | 0.9739 | |
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| 0.0018 | 17.0 | 5899 | 0.1851 | 0.8077 | 0.8212 | 0.8144 | 0.9741 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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