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# roberta-finetuned-gesture-prediction-21-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: 0.7782
- Accuracy: 0.8185
- Precision: 0.8116
- Recall: 0.8185
- F1: 0.8072

It achieves the following results on the evaluation set:
- Loss: 0.8142
- Accuracy: 0.8154
- Precision: 0.8189
- Recall: 0.8154
- F1: 0.8125

## 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-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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 2.2147        | 1.0   | 104  | 1.3857          | 0.7406   | 0.6887    | 0.7406 | 0.7013 |
| 1.2291        | 2.0   | 208  | 0.9750          | 0.7907   | 0.7597    | 0.7907 | 0.7618 |
| 0.836         | 3.0   | 312  | 0.8609          | 0.8028   | 0.7813    | 0.8028 | 0.7829 |
| 0.6129        | 4.0   | 416  | 0.8059          | 0.8078   | 0.8030    | 0.8078 | 0.7973 |
| 0.4747        | 5.0   | 520  | 0.7782          | 0.8185   | 0.8116    | 0.8185 | 0.8072 |
| 0.3639        | 6.0   | 624  | 0.7825          | 0.8175   | 0.8170    | 0.8175 | 0.8108 |
| 0.295         | 7.0   | 728  | 0.7913          | 0.8365   | 0.8283    | 0.8365 | 0.8280 |
| 0.236         | 8.0   | 832  | 0.7619          | 0.8273   | 0.8230    | 0.8273 | 0.8229 |
| 0.1989        | 9.0   | 936  | 0.7880          | 0.8309   | 0.8258    | 0.8309 | 0.8261 |
| 0.1879        | 10.0  | 1040 | 0.7915          | 0.8314   | 0.8247    | 0.8314 | 0.8264 |


### 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-21-classes", "metrics": ["accuracy", "precision", "recall", "f1"], "model-index": [{"name": "roberta-finetuned-gesture-prediction-21-classes", "results": []}]}
transformers pytorch tensorboard roberta token-classification generated_from_trainer dataset:qfrodicio/gesture-prediction-21-classes license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #roberta #token-classification #generated_from_trainer #dataset-qfrodicio/gesture-prediction-21-classes #license-mit #autotrain_compatible #endpoints_compatible #region-us 

roberta-finetuned-gesture-prediction-21-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: 0.7782
* Accuracy: 0.8185
* Precision: 0.8116
* Recall: 0.8185
* F1: 0.8072


It achieves the following results on the evaluation set:


* Loss: 0.8142
* Accuracy: 0.8154
* Precision: 0.8189
* Recall: 0.8154
* F1: 0.8125


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-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



### 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
* 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 ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #roberta #token-classification #generated_from_trainer #dataset-qfrodicio/gesture-prediction-21-classes #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### 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 ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #roberta #token-classification #generated_from_trainer #dataset-qfrodicio/gesture-prediction-21-classes #license-mit #autotrain_compatible #endpoints_compatible #region-us 
### 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### Framework versions


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