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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: gunghio/distilbert-base-multilingual-cased-finetuned-conll2003-ner |
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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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# gunghio/distilbert-base-multilingual-cased-finetuned-conll2003-ner |
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This model was trained from scratch on an unkown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0484 |
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- Precision: 0.9340 |
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- Recall: 0.9413 |
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- F1: 0.9376 |
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- Accuracy: 0.9875 |
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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: 3 |
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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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| 0.1931 | 1.0 | 878 | 0.0518 | 0.9146 | 0.9276 | 0.9210 | 0.9852 | |
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| 0.0389 | 2.0 | 1756 | 0.0470 | 0.9261 | 0.9389 | 0.9325 | 0.9870 | |
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| 0.0228 | 3.0 | 2634 | 0.0484 | 0.9340 | 0.9413 | 0.9376 | 0.9875 | |
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### Framework versions |
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- Transformers 4.6.1 |
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- Pytorch 1.8.1+cu101 |
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- Datasets 1.6.2 |
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- Tokenizers 0.10.2 |
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