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license: apache-2.0 |
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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: bert-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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# bert-finetuned-gesture-prediction-5-classes |
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This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset. |
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It achieves the following results on the validation set: |
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- Loss: 0.4958 |
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- Accuracy: 0.8636 |
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- Precision: 0.8662 |
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- Recall: 0.8636 |
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- F1: 0.8625 |
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It achieves the following results on the test set: |
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- Loss: 0.4599 |
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- Accuracy: 0.8561 |
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- Precision: 0.8578 |
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- Recall: 0.8561 |
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- F1: 0.8533 |
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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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- weight_decay: 0.01 |
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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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| 1.3816 | 1.0 | 71 | 0.6929 | 0.7820 | 0.7518 | 0.7820 | 0.7510 | |
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| 0.546 | 2.0 | 142 | 0.5128 | 0.8591 | 0.8614 | 0.8591 | 0.8579 | |
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| 0.3026 | 3.0 | 213 | 0.4958 | 0.8636 | 0.8662 | 0.8636 | 0.8625 | |
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| 0.1689 | 4.0 | 284 | 0.5090 | 0.8688 | 0.8694 | 0.8688 | 0.8678 | |
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| 0.1085 | 5.0 | 355 | 0.5306 | 0.8794 | 0.8813 | 0.8794 | 0.8786 | |
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| 0.0684 | 6.0 | 426 | 0.5516 | 0.8776 | 0.8774 | 0.8776 | 0.8765 | |
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| 0.0485 | 7.0 | 497 | 0.6051 | 0.8779 | 0.8794 | 0.8779 | 0.8770 | |
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| 0.0341 | 8.0 | 568 | 0.6224 | 0.8781 | 0.8780 | 0.8781 | 0.8776 | |
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| 0.0251 | 9.0 | 639 | 0.6429 | 0.8812 | 0.8817 | 0.8812 | 0.8805 | |
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| 0.021 | 10.0 | 710 | 0.6456 | 0.8807 | 0.8811 | 0.8807 | 0.8798 | |
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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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