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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: bert-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. -->
# bert-finetuned-gesture-prediction-9-classes
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
It achieves the following results on the validation set:
- Loss: 0.6948
- Accuracy: 0.8332
- Precision: 0.8352
- Recall: 0.8332
- F1: 0.8311
It achieves the following results on the test set:
- Loss: 0.6337
- Accuracy: 0.8297
- Precision: 0.8365
- Recall: 0.8297
- F1: 0.8281
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.6408 | 1.0 | 87 | 1.0168 | 0.7110 | 0.6825 | 0.7110 | 0.6559 |
| 0.7629 | 2.0 | 174 | 0.7777 | 0.7977 | 0.7863 | 0.7977 | 0.7856 |
| 0.4526 | 3.0 | 261 | 0.6951 | 0.8263 | 0.8276 | 0.8263 | 0.8199 |
| 0.285 | 4.0 | 348 | 0.6948 | 0.8332 | 0.8352 | 0.8332 | 0.8311 |
| 0.1788 | 5.0 | 435 | 0.7196 | 0.8277 | 0.8296 | 0.8277 | 0.8260 |
| 0.1246 | 6.0 | 522 | 0.7677 | 0.8314 | 0.8357 | 0.8314 | 0.8284 |
| 0.0866 | 7.0 | 609 | 0.7865 | 0.8407 | 0.8433 | 0.8407 | 0.8391 |
| 0.0629 | 8.0 | 696 | 0.8168 | 0.8435 | 0.8457 | 0.8435 | 0.8420 |
| 0.0489 | 9.0 | 783 | 0.8292 | 0.8417 | 0.8439 | 0.8417 | 0.8395 |
| 0.0398 | 10.0 | 870 | 0.8391 | 0.8443 | 0.8461 | 0.8443 | 0.8422 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
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