---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0350
- Precision: 0.8324
- Recall: 0.8324
- F1: 0.8324
- Accuracy: 0.8230

## 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: 4.9033776462709114e-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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.8808        | 1.0   | 104  | 1.1258          | 0.7513    | 0.7513 | 0.7513 | 0.7258   |
| 0.8843        | 2.0   | 208  | 0.9338          | 0.7765    | 0.7765 | 0.7765 | 0.7578   |
| 0.5881        | 3.0   | 312  | 0.8124          | 0.8173    | 0.8173 | 0.8173 | 0.8011   |
| 0.4017        | 4.0   | 416  | 0.8831          | 0.7973    | 0.7973 | 0.7973 | 0.7848   |
| 0.2652        | 5.0   | 520  | 0.9254          | 0.8300    | 0.8300 | 0.8300 | 0.8172   |
| 0.1776        | 6.0   | 624  | 0.9221          | 0.8310    | 0.8310 | 0.8310 | 0.8180   |
| 0.1234        | 7.0   | 728  | 1.0063          | 0.8211    | 0.8211 | 0.8211 | 0.8112   |
| 0.0829        | 8.0   | 832  | 1.0132          | 0.8298    | 0.8298 | 0.8298 | 0.8201   |
| 0.0552        | 9.0   | 936  | 1.0408          | 0.8290    | 0.8290 | 0.8290 | 0.8189   |
| 0.0409        | 10.0  | 1040 | 1.0350          | 0.8324    | 0.8324 | 0.8324 | 0.8230   |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1