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---
base_model: pysentimiento/robertuito-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: Robertuito-check-worthy-classifier
results: []
widget:
- text: "¿Es injusto que una persona que tenga UN MILLÓN DE EUROS en patrimonio pague 298 euros al año? Justicia fiscal es el camino para la justicia social /❤️ https://t.co/HRO5HRmceV"
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Robertuito-check-worthy-classifier
This model is a fine-tuned version of [pysentimiento/robertuito-base-uncased](https://huggingface.co/pysentimiento/robertuito-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2029
- F1 Class 0: 0.9557
- F1 Class 1: 0.6936
- F1: 0.8246
## 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: 0.0005
- 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
- lr_scheduler_warmup_ratio: 0.1
- lr_scheduler_warmup_steps: 200
- training_steps: 2000
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Class 0 | F1 Class 1 | F1 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:----------:|:------:|
| 0.4326 | 0.16 | 200 | 0.3187 | 0.9412 | 0.6514 | 0.7963 |
| 0.3765 | 0.32 | 400 | 0.2572 | 0.9323 | 0.6736 | 0.8030 |
| 0.3523 | 0.48 | 600 | 0.2079 | 0.9527 | 0.6990 | 0.8259 |
| 0.3594 | 0.64 | 800 | 0.2184 | 0.9505 | 0.5761 | 0.7633 |
| 0.3307 | 0.8 | 1000 | 0.2109 | 0.9497 | 0.6892 | 0.8194 |
| 0.3166 | 0.96 | 1200 | 0.2187 | 0.9537 | 0.6288 | 0.7912 |
| 0.297 | 1.13 | 1400 | 0.2541 | 0.9524 | 0.6429 | 0.7976 |
| 0.2766 | 1.29 | 1600 | 0.2031 | 0.9561 | 0.7173 | 0.8367 |
| 0.2628 | 1.45 | 1800 | 0.2076 | 0.9516 | 0.7200 | 0.8358 |
| 0.2313 | 1.61 | 2000 | 0.2029 | 0.9557 | 0.6936 | 0.8246 |
### Framework versions
- Transformers 4.35.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.14.1
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