---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: distilbert-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. -->

# distilbert-finetuned-gesture-prediction-21-classes

This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9212
- Accuracy: 0.8029
- Precision: 0.7978
- Recall: 0.8029
- F1: 0.7974

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 2.1942        | 1.0   | 104  | 1.3566          | 0.7113   | 0.6581    | 0.7113 | 0.6683 |
| 1.1713        | 2.0   | 208  | 1.0182          | 0.7626   | 0.7445    | 0.7626 | 0.7348 |
| 0.8285        | 3.0   | 312  | 0.9028          | 0.7789   | 0.7626    | 0.7789 | 0.7607 |
| 0.6374        | 4.0   | 416  | 0.8845          | 0.7959   | 0.7950    | 0.7959 | 0.7890 |
| 0.4991        | 5.0   | 520  | 0.8936          | 0.7997   | 0.7949    | 0.7997 | 0.7865 |
| 0.3908        | 6.0   | 624  | 0.8829          | 0.7910   | 0.7879    | 0.7910 | 0.7864 |
| 0.3234        | 7.0   | 728  | 0.9004          | 0.7946   | 0.7898    | 0.7946 | 0.7888 |
| 0.2688        | 8.0   | 832  | 0.8947          | 0.8047   | 0.7993    | 0.8047 | 0.7995 |
| 0.2392        | 9.0   | 936  | 0.9154          | 0.8024   | 0.7980    | 0.8024 | 0.7961 |
| 0.2103        | 10.0  | 1040 | 0.9212          | 0.8029   | 0.7978    | 0.8029 | 0.7974 |


### Framework versions

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