readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: bert-base-cased-finetuned-gesture_prediction
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # bert-base-cased-finetuned-gesture_prediction
  
  This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.3875
  - Precision: 0.6404
  - Recall: 0.7109
  - F1: 0.6738
  - Accuracy: 0.8135
  
  ## Model description
  
  More information needed
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  
  More information needed
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 2e-05
  - train_batch_size: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 30
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 104  | 1.3672          | 0.3313    | 0.4468 | 0.3805 | 0.6480   |
  | No log        | 2.0   | 208  | 0.9858          | 0.4122    | 0.5520 | 0.472  | 0.7532   |
  | No log        | 3.0   | 312  | 0.9603          | 0.4783    | 0.6070 | 0.5351 | 0.7648   |
  | No log        | 4.0   | 416  | 0.8777          | 0.5602    | 0.6643 | 0.6078 | 0.7952   |
  | 0.9471        | 5.0   | 520  | 0.8859          | 0.5827    | 0.6795 | 0.6274 | 0.8057   |
  | 0.9471        | 6.0   | 624  | 0.9515          | 0.5604    | 0.6620 | 0.6070 | 0.8000   |
  | 0.9471        | 7.0   | 728  | 1.0203          | 0.6142    | 0.6982 | 0.6535 | 0.8037   |
  | 0.9471        | 8.0   | 832  | 1.0422          | 0.6058    | 0.7029 | 0.6508 | 0.8085   |
  | 0.9471        | 9.0   | 936  | 1.0426          | 0.6227    | 0.7006 | 0.6593 | 0.8045   |
  | 0.1111        | 10.0  | 1040 | 1.1450          | 0.6229    | 0.7263 | 0.6706 | 0.8080   |
  | 0.1111        | 11.0  | 1144 | 1.1765          | 0.6580    | 0.7111 | 0.6835 | 0.8134   |
  | 0.1111        | 12.0  | 1248 | 1.1905          | 0.6396    | 0.7099 | 0.6729 | 0.8124   |
  | 0.1111        | 13.0  | 1352 | 1.1967          | 0.6148    | 0.7111 | 0.6594 | 0.8055   |
  | 0.1111        | 14.0  | 1456 | 1.2124          | 0.6415    | 0.7158 | 0.6766 | 0.8085   |
  | 0.0225        | 15.0  | 1560 | 1.2407          | 0.6351    | 0.7146 | 0.6725 | 0.8114   |
  | 0.0225        | 16.0  | 1664 | 1.2745          | 0.6391    | 0.7041 | 0.6700 | 0.8073   |
  | 0.0225        | 17.0  | 1768 | 1.2878          | 0.6466    | 0.7146 | 0.6789 | 0.8169   |
  | 0.0225        | 18.0  | 1872 | 1.3091          | 0.6412    | 0.7170 | 0.6770 | 0.8101   |
  | 0.0225        | 19.0  | 1976 | 1.3373          | 0.6490    | 0.7181 | 0.6818 | 0.8101   |
  | 0.0075        | 20.0  | 2080 | 1.3352          | 0.6448    | 0.7135 | 0.6774 | 0.8101   |
  | 0.0075        | 21.0  | 2184 | 1.3328          | 0.6477    | 0.7205 | 0.6822 | 0.8114   |
  | 0.0075        | 22.0  | 2288 | 1.3498          | 0.6610    | 0.7251 | 0.6916 | 0.8129   |
  | 0.0075        | 23.0  | 2392 | 1.3464          | 0.6606    | 0.7216 | 0.6898 | 0.8090   |
  | 0.0075        | 24.0  | 2496 | 1.3580          | 0.6551    | 0.7263 | 0.6889 | 0.8144   |
  | 0.0036        | 25.0  | 2600 | 1.3687          | 0.6547    | 0.7228 | 0.6870 | 0.8114   |
  | 0.0036        | 26.0  | 2704 | 1.3730          | 0.6471    | 0.7228 | 0.6829 | 0.8149   |
  | 0.0036        | 27.0  | 2808 | 1.3808          | 0.6505    | 0.7228 | 0.6848 | 0.8124   |
  | 0.0036        | 28.0  | 2912 | 1.3869          | 0.6603    | 0.7228 | 0.6901 | 0.8111   |
  | 0.0024        | 29.0  | 3016 | 1.3907          | 0.6624    | 0.7228 | 0.6913 | 0.8113   |
  | 0.0024        | 30.0  | 3120 | 1.3913          | 0.6667    | 0.7251 | 0.6947 | 0.8121   |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  