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---
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library_name: transformers
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license: cc-by-4.0
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base_model: NazaGara/NER-fine-tuned-BETO
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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: NER-finetuning-BETO-PRO
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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: 0.8403323602066023
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- name: Recall
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type: recall
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value: 0.8598345588235294
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- name: F1
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type: f1
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value: 0.8499716070414537
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- name: Accuracy
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type: accuracy
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value: 0.9712682866352591
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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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# NER-finetuning-BETO-PRO
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This model is a fine-tuned version of [NazaGara/NER-fine-tuned-BETO](https://huggingface.co/NazaGara/NER-fine-tuned-BETO) on the conll2002 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1541
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- Precision: 0.8403
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- Recall: 0.8598
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- F1: 0.8500
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- Accuracy: 0.9713
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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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs: 2
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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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| 0.0458 | 1.0 | 1041 | 0.1475 | 0.8485 | 0.8587 | 0.8536 | 0.9708 |
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| 0.0229 | 2.0 | 2082 | 0.1541 | 0.8403 | 0.8598 | 0.8500 | 0.9713 |
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### Framework versions
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- Transformers 4.46.2
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- Pytorch 2.5.1+cpu
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- Datasets 3.1.0
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- Tokenizers 0.20.3
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