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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- lextreme |
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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-mapa_fine-ner |
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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: lextreme |
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type: lextreme |
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config: mapa_fine |
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split: test |
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args: mapa_fine |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.8763335204941044 |
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- name: Recall |
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type: recall |
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value: 0.9115199299167762 |
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- name: F1 |
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type: f1 |
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value: 0.8935804766335075 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9956876979901592 |
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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-mapa_fine-ner |
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This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the lextreme dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0282 |
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- Precision: 0.8763 |
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- Recall: 0.9115 |
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- F1: 0.8936 |
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- Accuracy: 0.9957 |
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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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| 0.0244 | 1.0 | 1739 | 0.0202 | 0.8083 | 0.9314 | 0.8655 | 0.9941 | |
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| 0.0154 | 2.0 | 3478 | 0.0173 | 0.8813 | 0.9006 | 0.8908 | 0.9954 | |
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| 0.0118 | 3.0 | 5217 | 0.0161 | 0.8885 | 0.9131 | 0.9006 | 0.9960 | |
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| 0.0084 | 4.0 | 6956 | 0.0194 | 0.8485 | 0.9295 | 0.8871 | 0.9953 | |
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| 0.0069 | 5.0 | 8695 | 0.0219 | 0.8583 | 0.9198 | 0.8880 | 0.9953 | |
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| 0.0054 | 6.0 | 10434 | 0.0229 | 0.8622 | 0.9160 | 0.8883 | 0.9954 | |
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| 0.0032 | 7.0 | 12173 | 0.0248 | 0.8817 | 0.8979 | 0.8898 | 0.9956 | |
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| 0.0023 | 8.0 | 13912 | 0.0265 | 0.8900 | 0.9023 | 0.8961 | 0.9958 | |
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| 0.0018 | 9.0 | 15651 | 0.0275 | 0.8657 | 0.9137 | 0.8890 | 0.9954 | |
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| 0.0016 | 10.0 | 17390 | 0.0282 | 0.8763 | 0.9115 | 0.8936 | 0.9957 | |
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### Framework versions |
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- Transformers 4.26.0 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.9.0 |
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- Tokenizers 0.13.2 |
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