---
license: apache-2.0
tags:
- generated_from_trainer
datasets: qfrodicio/gesture-prediction-21-classes
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: 0.8430
- Accuracy: 0.8077
- Precision: 0.8063
- Recall: 0.8077
- F1: 0.8038

It achieves the following results on the test set:
- Loss: 0.8332
- Accuracy: 0.7934
- Precision: 0.7925
- Recall: 0.7934
- F1: 0.7875


## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

This 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 2.2082        | 1.0   | 104  | 1.3318          | 0.6956   | 0.6361    | 0.6956 | 0.6473 |
| 1.1512        | 2.0   | 208  | 1.0114          | 0.7604   | 0.7463    | 0.7604 | 0.7368 |
| 0.8152        | 3.0   | 312  | 0.8805          | 0.7860   | 0.7677    | 0.7860 | 0.7698 |
| 0.6142        | 4.0   | 416  | 0.8486          | 0.8025   | 0.8035    | 0.8025 | 0.7961 |
| 0.4726        | 5.0   | 520  | 0.8651          | 0.7992   | 0.7987    | 0.7992 | 0.7894 |
| 0.3677        | 6.0   | 624  | 0.8430          | 0.8077   | 0.8063    | 0.8077 | 0.8038 |
| 0.2967        | 7.0   | 728  | 0.8564          | 0.8037   | 0.8029    | 0.8037 | 0.7995 |
| 0.2494        | 8.0   | 832  | 0.8567          | 0.8077   | 0.8054    | 0.8077 | 0.8041 |
| 0.2163        | 9.0   | 936  | 0.8789          | 0.8075   | 0.8060    | 0.8075 | 0.8035 |
| 0.193         | 10.0  | 1040 | 0.8880          | 0.8077   | 0.8072    | 0.8077 | 0.8032 |


### Framework versions

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