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---
license: apache-2.0
tags:
- generated_from_trainer
datasets: qfrodicio/gesture-prediction-21-classes
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: bert-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. -->
# bert-finetuned-gesture-prediction-21-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: 0.8664
- Accuracy: 0.8123
- Precision: 0.8122
- Recall: 0.8123
- F1: 0.8048
It achieves the following results on the test set:
- Loss: 0.8381
- Accuracy: 0.7884
- Precision: 0.7954
- Recall: 0.7884
- F1: 0.7827
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 2.225 | 1.0 | 104 | 1.3314 | 0.7115 | 0.6469 | 0.7115 | 0.6675 |
| 1.0881 | 2.0 | 208 | 0.9569 | 0.7750 | 0.7577 | 0.7750 | 0.7525 |
| 0.7006 | 3.0 | 312 | 0.8805 | 0.7959 | 0.7917 | 0.7959 | 0.7831 |
| 0.4943 | 4.0 | 416 | 0.8664 | 0.8123 | 0.8122 | 0.8123 | 0.8048 |
| 0.3372 | 5.0 | 520 | 0.8765 | 0.8130 | 0.8102 | 0.8130 | 0.8053 |
| 0.2416 | 6.0 | 624 | 0.8772 | 0.8166 | 0.8139 | 0.8166 | 0.8107 |
| 0.178 | 7.0 | 728 | 0.9186 | 0.8217 | 0.8186 | 0.8217 | 0.8167 |
| 0.1302 | 8.0 | 832 | 0.9186 | 0.8202 | 0.8183 | 0.8202 | 0.8165 |
| 0.1063 | 9.0 | 936 | 0.9618 | 0.8245 | 0.8213 | 0.8245 | 0.8198 |
| 0.094 | 10.0 | 1040 | 0.9660 | 0.8214 | 0.8184 | 0.8214 | 0.8166 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
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