---
license: apache-2.0
base_model: distilbert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2008
- Precision: 0.7823
- Recall: 0.7823
- F1: 0.7823
- Accuracy: 0.7745

## 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: 9.96098704459956e-05
- train_batch_size: 64
- eval_batch_size: 64
- 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.4985        | 1.0   | 26   | 1.0570          | 0.7288    | 0.7288 | 0.7288 | 0.7177   |
| 0.2387        | 2.0   | 52   | 1.0720          | 0.7775    | 0.7775 | 0.7775 | 0.7672   |
| 0.1348        | 3.0   | 78   | 1.0681          | 0.7775    | 0.7775 | 0.7775 | 0.7682   |
| 0.0811        | 4.0   | 104  | 1.1143          | 0.7884    | 0.7884 | 0.7884 | 0.7781   |
| 0.0565        | 5.0   | 130  | 1.1128          | 0.7867    | 0.7867 | 0.7867 | 0.7783   |
| 0.0419        | 6.0   | 156  | 1.1051          | 0.7966    | 0.7966 | 0.7966 | 0.7880   |
| 0.0257        | 7.0   | 182  | 1.1567          | 0.7839    | 0.7839 | 0.7839 | 0.7737   |
| 0.0217        | 8.0   | 208  | 1.1675          | 0.7859    | 0.7859 | 0.7859 | 0.7757   |
| 0.0145        | 9.0   | 234  | 1.1976          | 0.7847    | 0.7847 | 0.7847 | 0.7769   |
| 0.0115        | 10.0  | 260  | 1.2008          | 0.7823    | 0.7823 | 0.7823 | 0.7745   |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1