update model card README.md
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README.md
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metrics:
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- name: Precision
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type: precision
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value: 0.
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- name: Recall
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type: recall
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value: 0.
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- name: F1
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type: f1
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value: 0.
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- name: Accuracy
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type: accuracy
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value: 0.
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language:
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- es
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pipeline_tag: token-classification
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widget:
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- text: "Guatemala sufre y llora a sus fallecidos bajo un manto negro de ceniza."
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- text: "La estrategia se ejecuta, no se cuenta."
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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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This model is a fine-tuned version of [filevich/robertita-cased](https://huggingface.co/filevich/robertita-cased) on the fact2020 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Precision: 0.
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- Recall: 0.
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- F1: 0.
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- Accuracy: 0.
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate:
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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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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| No log | 1.0 | 116 | 0.
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| No log | 2.0 | 232 | 0.
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| No log | 3.0 | 348 | 0.
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.1+cu117
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- Datasets 2.14.4
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- Tokenizers 0.13.3
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metrics:
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- name: Precision
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type: precision
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value: 0.9958259428424656
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- name: Recall
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type: recall
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value: 0.990818034441507
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- name: F1
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type: f1
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value: 0.9915358119908528
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- name: Accuracy
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type: accuracy
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value: 0.990818034441507
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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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This model is a fine-tuned version of [filevich/robertita-cased](https://huggingface.co/filevich/robertita-cased) on the fact2020 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0402
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- Precision: 0.9958
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- Recall: 0.9908
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- F1: 0.9915
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- Accuracy: 0.9908
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 6e-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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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| No log | 1.0 | 116 | 0.0372 | 0.9947 | 0.9889 | 0.9895 | 0.9889 |
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| No log | 2.0 | 232 | 0.0388 | 0.9961 | 0.9903 | 0.9913 | 0.9903 |
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| No log | 3.0 | 348 | 0.0402 | 0.9958 | 0.9908 | 0.9915 | 0.9908 |
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.1+cu117
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- Datasets 2.14.4
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- Tokenizers 0.13.3
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