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-21-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-21-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: 0.9818
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- Accuracy: 0.8232
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- Precision: 0.8213
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- Recall: 0.8232
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- F1: 0.8181
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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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| 2.1826 | 1.0 | 104 | 1.2892 | 0.7193 | 0.6656 | 0.7193 | 0.6745 |
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| 1.0758 | 2.0 | 208 | 0.9593 | 0.7816 | 0.7519 | 0.7816 | 0.7621 |
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| 0.6947 | 3.0 | 312 | 0.9170 | 0.7885 | 0.7730 | 0.7885 | 0.7760 |
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| 0.4928 | 4.0 | 416 | 0.8967 | 0.8014 | 0.7931 | 0.8014 | 0.7913 |
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| 0.3413 | 5.0 | 520 | 0.9195 | 0.8034 | 0.8076 | 0.8034 | 0.7966 |
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| 0.2473 | 6.0 | 624 | 0.9123 | 0.8131 | 0.8134 | 0.8131 | 0.8078 |
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| 0.1799 | 7.0 | 728 | 0.9474 | 0.8191 | 0.8195 | 0.8191 | 0.8139 |
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| 0.1329 | 8.0 | 832 | 0.9611 | 0.8237 | 0.8222 | 0.8237 | 0.8182 |
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| 0.116 | 9.0 | 936 | 0.9849 | 0.8204 | 0.8190 | 0.8204 | 0.8148 |
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| 0.0972 | 10.0 | 1040 | 0.9818 | 0.8232 | 0.8213 | 0.8232 | 0.8181 |
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### Framework versions
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