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--- |
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license: mit |
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tags: |
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- generated_from_trainer |
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datasets: qfrodicio/gesture-prediction-5-classes |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: roberta-finetuned-gesture-prediction-5-classes |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# roberta-finetuned-gesture-prediction-5-classes |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4764 |
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- Accuracy: 0.8729 |
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- Precision: 0.8731 |
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- Recall: 0.8729 |
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- F1: 0.8725 |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4842 |
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- Accuracy: 0.8628 |
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- Precision: 0.8629 |
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- Recall: 0.8628 |
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- F1: 0.8619 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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The model has been trained with the qfrodicio/gesture-prediction-5-classes dataset |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 1.4556 | 1.0 | 71 | 0.9405 | 0.6561 | 0.6129 | 0.6561 | 0.5981 | |
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| 0.7207 | 2.0 | 142 | 0.5276 | 0.8442 | 0.8463 | 0.8442 | 0.8406 | |
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| 0.4005 | 3.0 | 213 | 0.4997 | 0.8662 | 0.8719 | 0.8662 | 0.8640 | |
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| 0.2417 | 4.0 | 284 | 0.4764 | 0.8729 | 0.8731 | 0.8729 | 0.8725 | |
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| 0.1757 | 5.0 | 355 | 0.5135 | 0.8812 | 0.8827 | 0.8812 | 0.8810 | |
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| 0.1398 | 6.0 | 426 | 0.5266 | 0.8710 | 0.8710 | 0.8710 | 0.8704 | |
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| 0.0937 | 7.0 | 497 | 0.5438 | 0.8799 | 0.8801 | 0.8799 | 0.8792 | |
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| 0.07 | 8.0 | 568 | 0.5759 | 0.8769 | 0.8770 | 0.8769 | 0.8766 | |
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| 0.0552 | 9.0 | 639 | 0.6035 | 0.8745 | 0.8741 | 0.8745 | 0.8738 | |
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| 0.0478 | 10.0 | 710 | 0.5974 | 0.8778 | 0.8775 | 0.8778 | 0.8771 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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