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---
license: mit
tags:
- generated_from_trainer
datasets: qfrodicio/gesture-prediction-21-classes
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: roberta-finetuned-gesture-prediction-21-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-21-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: 0.7782
- Accuracy: 0.8185
- Precision: 0.8116
- Recall: 0.8185
- F1: 0.8072
It achieves the following results on the evaluation set:
- Loss: 0.8142
- Accuracy: 0.8154
- Precision: 0.8189
- Recall: 0.8154
- F1: 0.8125
## 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-21-classes dataset
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- weight_decay: 0.01
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 2.2147 | 1.0 | 104 | 1.3857 | 0.7406 | 0.6887 | 0.7406 | 0.7013 |
| 1.2291 | 2.0 | 208 | 0.9750 | 0.7907 | 0.7597 | 0.7907 | 0.7618 |
| 0.836 | 3.0 | 312 | 0.8609 | 0.8028 | 0.7813 | 0.8028 | 0.7829 |
| 0.6129 | 4.0 | 416 | 0.8059 | 0.8078 | 0.8030 | 0.8078 | 0.7973 |
| 0.4747 | 5.0 | 520 | 0.7782 | 0.8185 | 0.8116 | 0.8185 | 0.8072 |
| 0.3639 | 6.0 | 624 | 0.7825 | 0.8175 | 0.8170 | 0.8175 | 0.8108 |
| 0.295 | 7.0 | 728 | 0.7913 | 0.8365 | 0.8283 | 0.8365 | 0.8280 |
| 0.236 | 8.0 | 832 | 0.7619 | 0.8273 | 0.8230 | 0.8273 | 0.8229 |
| 0.1989 | 9.0 | 936 | 0.7880 | 0.8309 | 0.8258 | 0.8309 | 0.8261 |
| 0.1879 | 10.0 | 1040 | 0.7915 | 0.8314 | 0.8247 | 0.8314 | 0.8264 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
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