update model card README.md
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README.md
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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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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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 evaluation set:
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- Loss: 0.
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate:
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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:
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
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### Framework versions
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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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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 evaluation set:
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- Loss: 0.8391
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- Accuracy: 0.8443
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- Precision: 0.8461
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- Recall: 0.8443
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- F1: 0.8422
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## Model description
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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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| 1.6408 | 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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