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---
base_model: MMG/mlm-spanish-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: roberta-finetuned-gesture-prediction-es
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. -->
# roberta-finetuned-gesture-prediction-es
This model is a fine-tuned version of [MMG/mlm-spanish-roberta-base](https://huggingface.co/MMG/mlm-spanish-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7706
- Accuracy: 0.7223
- Precision: 0.7215
- Recall: 0.7223
- F1: 0.7156
## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.8523 | 1.0 | 102 | 1.2237 | 0.6618 | 0.6205 | 0.6618 | 0.6316 |
| 1.0093 | 2.0 | 204 | 1.1357 | 0.6886 | 0.6715 | 0.6886 | 0.6663 |
| 0.6999 | 3.0 | 306 | 1.1758 | 0.6884 | 0.7008 | 0.6884 | 0.6763 |
| 0.4872 | 4.0 | 408 | 1.1398 | 0.6955 | 0.6982 | 0.6955 | 0.6839 |
| 0.3198 | 5.0 | 510 | 1.2017 | 0.7096 | 0.7112 | 0.7096 | 0.7059 |
| 0.2414 | 6.0 | 612 | 1.2819 | 0.7152 | 0.7101 | 0.7152 | 0.7049 |
| 0.1676 | 7.0 | 714 | 1.3279 | 0.7299 | 0.7272 | 0.7299 | 0.7221 |
| 0.1245 | 8.0 | 816 | 1.4593 | 0.7098 | 0.7078 | 0.7098 | 0.7011 |
| 0.0843 | 9.0 | 918 | 1.5682 | 0.7134 | 0.7131 | 0.7134 | 0.7063 |
| 0.0636 | 10.0 | 1020 | 1.5447 | 0.7195 | 0.7161 | 0.7195 | 0.7128 |
| 0.0464 | 11.0 | 1122 | 1.6686 | 0.7118 | 0.7164 | 0.7118 | 0.7050 |
| 0.0367 | 12.0 | 1224 | 1.6438 | 0.7251 | 0.7252 | 0.7251 | 0.7181 |
| 0.0292 | 13.0 | 1326 | 1.6803 | 0.7232 | 0.7199 | 0.7232 | 0.7170 |
| 0.0227 | 14.0 | 1428 | 1.6852 | 0.7217 | 0.7193 | 0.7217 | 0.7157 |
| 0.0155 | 15.0 | 1530 | 1.7753 | 0.7219 | 0.7245 | 0.7219 | 0.7156 |
| 0.0123 | 16.0 | 1632 | 1.7875 | 0.7157 | 0.7149 | 0.7157 | 0.7085 |
| 0.0102 | 17.0 | 1734 | 1.7649 | 0.7159 | 0.7148 | 0.7159 | 0.7095 |
| 0.0076 | 18.0 | 1836 | 1.7740 | 0.7204 | 0.7201 | 0.7204 | 0.7141 |
| 0.0074 | 19.0 | 1938 | 1.7674 | 0.7244 | 0.7235 | 0.7244 | 0.7177 |
| 0.0061 | 20.0 | 2040 | 1.7706 | 0.7223 | 0.7215 | 0.7223 | 0.7156 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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