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---
license: mit
tags:
- generated_from_trainer
datasets: qfrodicio/gesture-prediction-5-classes
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: roberta-finetuned-gesture-prediction-5-classes
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-5-classes
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4764
- Accuracy: 0.8729
- Precision: 0.8731
- Recall: 0.8729
- F1: 0.8725
It achieves the following results on the evaluation set:
- Loss: 0.4842
- Accuracy: 0.8628
- Precision: 0.8629
- Recall: 0.8628
- F1: 0.8619
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
The model has been trained with the qfrodicio/gesture-prediction-5-classes dataset
## 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.4556 | 1.0 | 71 | 0.9405 | 0.6561 | 0.6129 | 0.6561 | 0.5981 |
| 0.7207 | 2.0 | 142 | 0.5276 | 0.8442 | 0.8463 | 0.8442 | 0.8406 |
| 0.4005 | 3.0 | 213 | 0.4997 | 0.8662 | 0.8719 | 0.8662 | 0.8640 |
| 0.2417 | 4.0 | 284 | 0.4764 | 0.8729 | 0.8731 | 0.8729 | 0.8725 |
| 0.1757 | 5.0 | 355 | 0.5135 | 0.8812 | 0.8827 | 0.8812 | 0.8810 |
| 0.1398 | 6.0 | 426 | 0.5266 | 0.8710 | 0.8710 | 0.8710 | 0.8704 |
| 0.0937 | 7.0 | 497 | 0.5438 | 0.8799 | 0.8801 | 0.8799 | 0.8792 |
| 0.07 | 8.0 | 568 | 0.5759 | 0.8769 | 0.8770 | 0.8769 | 0.8766 |
| 0.0552 | 9.0 | 639 | 0.6035 | 0.8745 | 0.8741 | 0.8745 | 0.8738 |
| 0.0478 | 10.0 | 710 | 0.5974 | 0.8778 | 0.8775 | 0.8778 | 0.8771 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
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