--- base_model: dccuchile/bert-base-spanish-wwm-cased tags: - generated_from_trainer datasets: - fact2020 metrics: - precision - recall - f1 - accuracy model-index: - name: beto-finetuned-fact results: - task: name: Token Classification type: token-classification dataset: name: fact2020 type: fact2020 config: fact2020 split: validation args: fact2020 metrics: - name: Precision type: precision value: 0.9949051696399874 - name: Recall type: recall value: 0.9894945851054298 - name: F1 type: f1 value: 0.9900110805842972 - name: Accuracy type: accuracy value: 0.9894945851054298 language: - es pipeline_tag: token-classification widget: - text: "Guatemala sufre y llora a sus fallecidos bajo un manto negro de ceniza." - text: "La estrategia se ejecuta, no se cuenta." --- # beto-finetuned-fact This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-cased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased) on the fact2020 dataset. It achieves the following results on the evaluation set: - Loss: 0.0422 - Precision: 0.9949 - Recall: 0.9895 - F1: 0.9900 - Accuracy: 0.9895 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | No log | 1.0 | 116 | 0.0437 | 0.9943 | 0.9883 | 0.9889 | 0.9883 | | No log | 2.0 | 232 | 0.0432 | 0.9949 | 0.9894 | 0.9900 | 0.9894 | | No log | 3.0 | 348 | 0.0422 | 0.9949 | 0.9895 | 0.9900 | 0.9895 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu117 - Datasets 2.14.4 - Tokenizers 0.13.3