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--- |
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license: apache-2.0 |
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base_model: BSC-LT/roberta-base-bne-capitel-ner |
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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: roberta-base-bne-capitel-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: 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: 0.8712310133756518 |
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- name: Recall |
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type: recall |
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value: 0.8830422794117647 |
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- name: F1 |
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type: f1 |
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value: 0.8770968846285518 |
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- name: Accuracy |
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type: accuracy |
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value: 0.978961189654646 |
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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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# roberta-base-bne-capitel-ner |
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This model is a fine-tuned version of [BSC-LT/roberta-base-bne-capitel-ner](https://huggingface.co/BSC-LT/roberta-base-bne-capitel-ner) on the conll2002 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1255 |
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- Precision: 0.8712 |
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- Recall: 0.8830 |
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- F1: 0.8771 |
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- Accuracy: 0.9790 |
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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: 8 |
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- eval_batch_size: 8 |
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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: 4 |
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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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| 0.0135 | 1.0 | 1041 | 0.1233 | 0.8615 | 0.8803 | 0.8708 | 0.9783 | |
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| 0.0111 | 2.0 | 2082 | 0.1099 | 0.8709 | 0.8853 | 0.8781 | 0.9799 | |
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| 0.0061 | 3.0 | 3123 | 0.1203 | 0.8569 | 0.8739 | 0.8653 | 0.9781 | |
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| 0.0035 | 4.0 | 4164 | 0.1255 | 0.8712 | 0.8830 | 0.8771 | 0.9790 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.4 |
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- Tokenizers 0.14.1 |
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