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--- |
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license: apache-2.0 |
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base_model: google-bert/bert-base-multilingual-uncased |
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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-base-multilingual-uncased-finetuned-ner-geocorpus |
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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-base-multilingual-uncased-finetuned-ner-geocorpus |
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This model is a fine-tuned version of [google-bert/bert-base-multilingual-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1210 |
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- Precision: 0.8205 |
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- Recall: 0.8757 |
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- F1: 0.8472 |
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- Accuracy: 0.9760 |
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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: 16 |
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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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| No log | 1.0 | 276 | 0.1670 | 0.7138 | 0.6690 | 0.6906 | 0.9555 | |
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| 0.247 | 2.0 | 552 | 0.1192 | 0.8109 | 0.7770 | 0.7936 | 0.9676 | |
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| 0.247 | 3.0 | 828 | 0.1181 | 0.8226 | 0.8188 | 0.8207 | 0.9709 | |
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| 0.0846 | 4.0 | 1104 | 0.1162 | 0.7656 | 0.8571 | 0.8088 | 0.9685 | |
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| 0.0846 | 5.0 | 1380 | 0.1248 | 0.7627 | 0.8699 | 0.8128 | 0.9687 | |
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| 0.0442 | 6.0 | 1656 | 0.0982 | 0.8233 | 0.8931 | 0.8568 | 0.9777 | |
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| 0.0442 | 7.0 | 1932 | 0.1114 | 0.8100 | 0.8862 | 0.8464 | 0.9741 | |
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| 0.0247 | 8.0 | 2208 | 0.1164 | 0.8342 | 0.8885 | 0.8605 | 0.9780 | |
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| 0.0247 | 9.0 | 2484 | 0.1208 | 0.7983 | 0.8920 | 0.8426 | 0.9746 | |
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| 0.0159 | 10.0 | 2760 | 0.1210 | 0.8205 | 0.8757 | 0.8472 | 0.9760 | |
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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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