---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-gesture-prediction-9-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. -->

# bert-finetuned-gesture-prediction-9-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 evaluation set:
- Loss: 0.6739
- Precision: 0.6215
- Recall: 0.7431
- F1: 0.6769
- Accuracy: 0.8366

## 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: 9.177375858742942e-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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.14          | 1.0   | 87   | 0.7099          | 0.5       | 0.6526 | 0.5662 | 0.8024   |
| 0.4501        | 2.0   | 174  | 0.6451          | 0.5944    | 0.7168 | 0.6499 | 0.8271   |
| 0.1964        | 3.0   | 261  | 0.6739          | 0.6215    | 0.7431 | 0.6769 | 0.8366   |


### Framework versions

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