|
--- |
|
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 |
|
|
