---
license: mit
tags:
- generated_from_trainer
datasets: qfrodicio/gesture-prediction-21-classes
metrics:
- accuracy
- precision
- recall
- f1
base_model: roberta-base
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