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--- |
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license: mit |
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base_model: filevich/robertita-cased |
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tags: |
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- generated_from_trainer |
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datasets: |
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- fact2020 |
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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: robertita-cased-finetuned-fact |
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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: fact2020 |
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type: fact2020 |
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config: fact2020 |
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split: validation |
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args: fact2020 |
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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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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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should probably proofread and complete it, then remove this comment. --> |
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# robertita-cased-finetuned-fact |
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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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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: 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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- 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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| 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 |
