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---
base_model: pysentimiento/robertuito-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
- recall
- accuracy
model-index:
- name: robertuito-finetuned-class
results: []
---
<!-- 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-finetuned-class
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: 0.6600
- F1: 0.7394
- Recall: 0.7425
- Accuracy: 0.7564
## 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: 2.989919952299843e-05
- train_batch_size: 64
- eval_batch_size: 32
- seed: 15
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Recall | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:--------:|
| No log | 1.0 | 87 | 0.7059 | 0.6831 | 0.6717 | 0.7315 |
| No log | 2.0 | 174 | 0.6123 | 0.7420 | 0.7442 | 0.7629 |
| No log | 3.0 | 261 | 0.6600 | 0.7394 | 0.7425 | 0.7564 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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