---
license: mit
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 the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7768
- Precision: 0.5980
- Recall: 0.7114
- F1: 0.6498
- Accuracy: 0.8114

## 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: 9.453261348481077e-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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.7887        | 1.0   | 104  | 1.0084          | 0.4610    | 0.5990 | 0.5210 | 0.7479   |
| 0.8935        | 2.0   | 208  | 0.8393          | 0.5249    | 0.6618 | 0.5855 | 0.7872   |
| 0.5383        | 3.0   | 312  | 0.7661          | 0.5499    | 0.6860 | 0.6104 | 0.7919   |
| 0.3124        | 4.0   | 416  | 0.7768          | 0.5980    | 0.7114 | 0.6498 | 0.8114   |


### Framework versions

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