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# roberta-finetuned-gesture-prediction-5-classes

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4764
- Accuracy: 0.8729
- Precision: 0.8731
- Recall: 0.8729
- F1: 0.8725

It achieves the following results on the evaluation set:
- Loss: 0.4842
- Accuracy: 0.8628
- Precision: 0.8629
- Recall: 0.8628
- F1: 0.8619

## 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-5-classes dataset

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.4556        | 1.0   | 71   | 0.9405          | 0.6561   | 0.6129    | 0.6561 | 0.5981 |
| 0.7207        | 2.0   | 142  | 0.5276          | 0.8442   | 0.8463    | 0.8442 | 0.8406 |
| 0.4005        | 3.0   | 213  | 0.4997          | 0.8662   | 0.8719    | 0.8662 | 0.8640 |
| 0.2417        | 4.0   | 284  | 0.4764          | 0.8729   | 0.8731    | 0.8729 | 0.8725 |
| 0.1757        | 5.0   | 355  | 0.5135          | 0.8812   | 0.8827    | 0.8812 | 0.8810 |
| 0.1398        | 6.0   | 426  | 0.5266          | 0.8710   | 0.8710    | 0.8710 | 0.8704 |
| 0.0937        | 7.0   | 497  | 0.5438          | 0.8799   | 0.8801    | 0.8799 | 0.8792 |
| 0.07          | 8.0   | 568  | 0.5759          | 0.8769   | 0.8770    | 0.8769 | 0.8766 |
| 0.0552        | 9.0   | 639  | 0.6035          | 0.8745   | 0.8741    | 0.8745 | 0.8738 |
| 0.0478        | 10.0  | 710  | 0.5974          | 0.8778   | 0.8775    | 0.8778 | 0.8771 |


### Framework versions

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

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": "qfrodicio/gesture-prediction-5-classes", "metrics": ["accuracy", "precision", "recall", "f1"], "model-index": [{"name": "roberta-finetuned-gesture-prediction-5-classes", "results": []}]}
transformers pytorch tensorboard safetensors roberta token-classification generated_from_trainer dataset:qfrodicio/gesture-prediction-5-classes license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #safetensors #roberta #token-classification #generated_from_trainer #dataset-qfrodicio/gesture-prediction-5-classes #license-mit #autotrain_compatible #endpoints_compatible #region-us 

roberta-finetuned-gesture-prediction-5-classes
==============================================


This model is a fine-tuned version of roberta-base on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.4764
* Accuracy: 0.8729
* Precision: 0.8731
* Recall: 0.8729
* F1: 0.8725


It achieves the following results on the evaluation set:


* Loss: 0.4842
* Accuracy: 0.8628
* Precision: 0.8629
* Recall: 0.8628
* F1: 0.8619


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-5-classes dataset


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



### Framework versions


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



### 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 ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #safetensors #roberta #token-classification #generated_from_trainer #dataset-qfrodicio/gesture-prediction-5-classes #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### 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 ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #safetensors #roberta #token-classification #generated_from_trainer #dataset-qfrodicio/gesture-prediction-5-classes #license-mit #autotrain_compatible #endpoints_compatible #region-us 
### 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### Framework versions


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