---
license: mit
tags:
- generated_from_trainer
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: 0.9312
- Accuracy: 0.8163
- Precision: 0.8090
- Recall: 0.8163
- F1: 0.8108

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 2.2472        | 1.0   | 104  | 1.4263          | 0.7364   | 0.6666    | 0.7364 | 0.6921 |
| 1.2677        | 2.0   | 208  | 1.0547          | 0.7888   | 0.7581    | 0.7888 | 0.7638 |
| 0.8676        | 3.0   | 312  | 0.9315          | 0.7963   | 0.7775    | 0.7963 | 0.7791 |
| 0.6407        | 4.0   | 416  | 0.9022          | 0.8102   | 0.8012    | 0.8102 | 0.7995 |
| 0.4926        | 5.0   | 520  | 0.8994          | 0.8120   | 0.8080    | 0.8120 | 0.8016 |
| 0.3754        | 6.0   | 624  | 0.9018          | 0.8069   | 0.7999    | 0.8069 | 0.8002 |
| 0.3037        | 7.0   | 728  | 0.9048          | 0.8131   | 0.8055    | 0.8131 | 0.8060 |
| 0.2499        | 8.0   | 832  | 0.9030          | 0.8161   | 0.8119    | 0.8161 | 0.8117 |
| 0.2155        | 9.0   | 936  | 0.9279          | 0.8160   | 0.8088    | 0.8160 | 0.8106 |
| 0.2062        | 10.0  | 1040 | 0.9312          | 0.8163   | 0.8090    | 0.8163 | 0.8108 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2