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--- |
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license: apache-2.0 |
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base_model: distilbert/distilbert-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: distilbert-base-multilingual-cased-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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# distilbert-base-multilingual-cased-finetuned-ner-geocorpus |
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This model is a fine-tuned version of [distilbert/distilbert-base-multilingual-cased](https://huggingface.co/distilbert/distilbert-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: 0.1028 |
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- Precision: 0.8079 |
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- Recall: 0.8868 |
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- F1: 0.8455 |
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- Accuracy: 0.9747 |
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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: 100 |
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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 | 0.1866 | 0.7323 | 0.6760 | 0.7030 | 0.9551 | |
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| 0.2877 | 2.0 | 552 | 0.1247 | 0.7870 | 0.7788 | 0.7829 | 0.9685 | |
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| 0.2877 | 3.0 | 828 | 0.1125 | 0.8547 | 0.7819 | 0.8167 | 0.9719 | |
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| 0.0858 | 4.0 | 1104 | 0.1043 | 0.8274 | 0.8463 | 0.8368 | 0.9739 | |
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| 0.0858 | 5.0 | 1380 | 0.1062 | 0.8349 | 0.8349 | 0.8349 | 0.9730 | |
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| 0.0424 | 6.0 | 1656 | 0.1028 | 0.8079 | 0.8868 | 0.8455 | 0.9747 | |
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| 0.0424 | 7.0 | 1932 | 0.1139 | 0.8586 | 0.8702 | 0.8644 | 0.9769 | |
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| 0.0225 | 8.0 | 2208 | 0.1229 | 0.8511 | 0.9024 | 0.8760 | 0.9765 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 2.1.2 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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