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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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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-9-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-9-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: 0.6948 |
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- Accuracy: 0.8332 |
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- Precision: 0.8352 |
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- Recall: 0.8332 |
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- F1: 0.8311 |
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It achieves the following results on the test set: |
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- Loss: 0.6337 |
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- Accuracy: 0.8297 |
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- Precision: 0.8365 |
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- Recall: 0.8297 |
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- F1: 0.8281 |
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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-9-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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| 1.6408 | 1.0 | 87 | 1.0168 | 0.7110 | 0.6825 | 0.7110 | 0.6559 | |
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| 0.7629 | 2.0 | 174 | 0.7777 | 0.7977 | 0.7863 | 0.7977 | 0.7856 | |
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| 0.4526 | 3.0 | 261 | 0.6951 | 0.8263 | 0.8276 | 0.8263 | 0.8199 | |
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| 0.285 | 4.0 | 348 | 0.6948 | 0.8332 | 0.8352 | 0.8332 | 0.8311 | |
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| 0.1788 | 5.0 | 435 | 0.7196 | 0.8277 | 0.8296 | 0.8277 | 0.8260 | |
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| 0.1246 | 6.0 | 522 | 0.7677 | 0.8314 | 0.8357 | 0.8314 | 0.8284 | |
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| 0.0866 | 7.0 | 609 | 0.7865 | 0.8407 | 0.8433 | 0.8407 | 0.8391 | |
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| 0.0629 | 8.0 | 696 | 0.8168 | 0.8435 | 0.8457 | 0.8435 | 0.8420 | |
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| 0.0489 | 9.0 | 783 | 0.8292 | 0.8417 | 0.8439 | 0.8417 | 0.8395 | |
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| 0.0398 | 10.0 | 870 | 0.8391 | 0.8443 | 0.8461 | 0.8443 | 0.8422 | |
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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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