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library_name: transformers
base_model: pysentimiento/robertuito-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
- recall
model-index:
- name: test_trainer
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# test_trainer
This model is a fine-tuned version of [pysentimiento/robertuito-base-uncased](https://huggingface.co/pysentimiento/robertuito-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0158
- F1: 0.9987
- Recall: 0.9987
## 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: 5e-05
- train_batch_size: 64
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Recall |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| No log | 1.0 | 95 | 0.0224 | 0.9960 | 0.9960 |
| No log | 2.0 | 190 | 0.0103 | 0.9987 | 0.9987 |
| No log | 3.0 | 285 | 0.0109 | 0.9987 | 0.9987 |
| No log | 4.0 | 380 | 0.0198 | 0.9974 | 0.9973 |
| No log | 5.0 | 475 | 0.0130 | 0.9987 | 0.9987 |
| 0.0139 | 6.0 | 570 | 0.0130 | 0.9987 | 0.9987 |
| 0.0139 | 7.0 | 665 | 0.0131 | 0.9987 | 0.9987 |
| 0.0139 | 8.0 | 760 | 0.0133 | 0.9987 | 0.9987 |
| 0.0139 | 9.0 | 855 | 0.0134 | 0.9987 | 0.9987 |
| 0.0139 | 10.0 | 950 | 0.0136 | 0.9987 | 0.9987 |
| 0.0 | 11.0 | 1045 | 0.0137 | 0.9987 | 0.9987 |
| 0.0 | 12.0 | 1140 | 0.0138 | 0.9987 | 0.9987 |
| 0.0 | 13.0 | 1235 | 0.0138 | 0.9987 | 0.9987 |
| 0.0 | 14.0 | 1330 | 0.0140 | 0.9987 | 0.9987 |
| 0.0 | 15.0 | 1425 | 0.0141 | 0.9987 | 0.9987 |
| 0.0 | 16.0 | 1520 | 0.0142 | 0.9987 | 0.9987 |
| 0.0 | 17.0 | 1615 | 0.0143 | 0.9987 | 0.9987 |
| 0.0 | 18.0 | 1710 | 0.0144 | 0.9987 | 0.9987 |
| 0.0 | 19.0 | 1805 | 0.0145 | 0.9987 | 0.9987 |
| 0.0 | 20.0 | 1900 | 0.0146 | 0.9987 | 0.9987 |
| 0.0 | 21.0 | 1995 | 0.0147 | 0.9987 | 0.9987 |
| 0.0 | 22.0 | 2090 | 0.0147 | 0.9987 | 0.9987 |
| 0.0 | 23.0 | 2185 | 0.0148 | 0.9987 | 0.9987 |
| 0.0 | 24.0 | 2280 | 0.0149 | 0.9987 | 0.9987 |
| 0.0 | 25.0 | 2375 | 0.0150 | 0.9987 | 0.9987 |
| 0.0 | 26.0 | 2470 | 0.0151 | 0.9987 | 0.9987 |
| 0.0 | 27.0 | 2565 | 0.0151 | 0.9987 | 0.9987 |
| 0.0 | 28.0 | 2660 | 0.0152 | 0.9987 | 0.9987 |
| 0.0 | 29.0 | 2755 | 0.0152 | 0.9987 | 0.9987 |
| 0.0 | 30.0 | 2850 | 0.0153 | 0.9987 | 0.9987 |
| 0.0 | 31.0 | 2945 | 0.0153 | 0.9987 | 0.9987 |
| 0.0 | 32.0 | 3040 | 0.0154 | 0.9987 | 0.9987 |
| 0.0 | 33.0 | 3135 | 0.0155 | 0.9987 | 0.9987 |
| 0.0 | 34.0 | 3230 | 0.0154 | 0.9987 | 0.9987 |
| 0.0 | 35.0 | 3325 | 0.0154 | 0.9987 | 0.9987 |
| 0.0 | 36.0 | 3420 | 0.0155 | 0.9987 | 0.9987 |
| 0.0 | 37.0 | 3515 | 0.0155 | 0.9987 | 0.9987 |
| 0.0 | 38.0 | 3610 | 0.0156 | 0.9987 | 0.9987 |
| 0.0 | 39.0 | 3705 | 0.0156 | 0.9987 | 0.9987 |
| 0.0 | 40.0 | 3800 | 0.0156 | 0.9987 | 0.9987 |
| 0.0 | 41.0 | 3895 | 0.0155 | 0.9987 | 0.9987 |
| 0.0 | 42.0 | 3990 | 0.0156 | 0.9987 | 0.9987 |
| 0.0 | 43.0 | 4085 | 0.0156 | 0.9987 | 0.9987 |
| 0.0 | 44.0 | 4180 | 0.0156 | 0.9987 | 0.9987 |
| 0.0 | 45.0 | 4275 | 0.0157 | 0.9987 | 0.9987 |
| 0.0 | 46.0 | 4370 | 0.0157 | 0.9987 | 0.9987 |
| 0.0 | 47.0 | 4465 | 0.0157 | 0.9987 | 0.9987 |
| 0.0 | 48.0 | 4560 | 0.0158 | 0.9987 | 0.9987 |
| 0.0 | 49.0 | 4655 | 0.0158 | 0.9987 | 0.9987 |
| 0.0 | 50.0 | 4750 | 0.0158 | 0.9987 | 0.9987 |
### Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
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