---
license: apache-2.0
tags:
- generated_from_trainer
datasets: qfrodicio/gesture-prediction-21-classes
metrics:
- accuracy
- precision
- recall
- f1
base_model: bert-base-cased
model-index:
- name: bert-finetuned-gesture-prediction-21-classes
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-finetuned-gesture-prediction-21-classes

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
It achieves the following results on the validation set:
- Loss: 0.8664
- Accuracy: 0.8123
- Precision: 0.8122
- Recall: 0.8123
- F1: 0.8048

It achieves the following results on the test set:
- Loss: 0.8381
- Accuracy: 0.7884
- Precision: 0.7954
- Recall: 0.7884
- F1: 0.7827

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 2.225         | 1.0   | 104  | 1.3314          | 0.7115   | 0.6469    | 0.7115 | 0.6675 |
| 1.0881        | 2.0   | 208  | 0.9569          | 0.7750   | 0.7577    | 0.7750 | 0.7525 |
| 0.7006        | 3.0   | 312  | 0.8805          | 0.7959   | 0.7917    | 0.7959 | 0.7831 |
| 0.4943        | 4.0   | 416  | 0.8664          | 0.8123   | 0.8122    | 0.8123 | 0.8048 |
| 0.3372        | 5.0   | 520  | 0.8765          | 0.8130   | 0.8102    | 0.8130 | 0.8053 |
| 0.2416        | 6.0   | 624  | 0.8772          | 0.8166   | 0.8139    | 0.8166 | 0.8107 |
| 0.178         | 7.0   | 728  | 0.9186          | 0.8217   | 0.8186    | 0.8217 | 0.8167 |
| 0.1302        | 8.0   | 832  | 0.9186          | 0.8202   | 0.8183    | 0.8202 | 0.8165 |
| 0.1063        | 9.0   | 936  | 0.9618          | 0.8245   | 0.8213    | 0.8245 | 0.8198 |
| 0.094         | 10.0  | 1040 | 0.9660          | 0.8214   | 0.8184    | 0.8214 | 0.8166 |


### Framework versions

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