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---
license: mit
tags:
- generated_from_trainer
datasets: qfrodicio/gesture-prediction-9-classes
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: roberta-finetuned-gesture-prediction-9-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. -->
# roberta-finetuned-gesture-prediction-9-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 validation set:
- Loss: 0.6668
- Accuracy: 0.8289
- Precision: 0.8288
- Recall: 0.8289
- F1: 0.8258
It achieves the following results on the test set:
- Loss: 0.6158
- Accuracy: 0.83
- Precision: 0.8296
- Recall: 0.83
- F1: 0.8274
## 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-9-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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.7138 | 1.0 | 87 | 1.0975 | 0.6915 | 0.6290 | 0.6915 | 0.6303 |
| 0.846 | 2.0 | 174 | 0.7497 | 0.7948 | 0.7790 | 0.7948 | 0.7772 |
| 0.5545 | 3.0 | 261 | 0.7078 | 0.8020 | 0.8000 | 0.8020 | 0.7927 |
| 0.3955 | 4.0 | 348 | 0.6668 | 0.8289 | 0.8288 | 0.8289 | 0.8258 |
| 0.279 | 5.0 | 435 | 0.6922 | 0.8291 | 0.8340 | 0.8291 | 0.8277 |
| 0.2203 | 6.0 | 522 | 0.6955 | 0.8373 | 0.8390 | 0.8373 | 0.8336 |
| 0.1595 | 7.0 | 609 | 0.7149 | 0.8395 | 0.8405 | 0.8395 | 0.8365 |
| 0.1349 | 8.0 | 696 | 0.7065 | 0.8436 | 0.8447 | 0.8436 | 0.8399 |
| 0.1047 | 9.0 | 783 | 0.7408 | 0.8481 | 0.8502 | 0.8481 | 0.8445 |
| 0.0906 | 10.0 | 870 | 0.7439 | 0.8495 | 0.8501 | 0.8495 | 0.8465 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
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