readme: ---
  license: mit
  tags:
  - generated_from_trainer
  model-index:
  - name: predict-perception-bert-cause-human
    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. -->
  
  # predict-perception-bert-cause-human
  
  This model is a fine-tuned version of [dbmdz/bert-base-italian-xxl-cased](https://huggingface.co/dbmdz/bert-base-italian-xxl-cased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7139
  - Rmse: 1.2259
  - Rmse Cause::a Causata da un essere umano: 1.2259
  - Mae: 1.0480
  - Mae Cause::a Causata da un essere umano: 1.0480
  - R2: 0.4563
  - R2 Cause::a Causata da un essere umano: 0.4563
  - Cos: 0.4783
  - Pair: 0.0
  - Rank: 0.5
  - Neighbors: 0.3953
  - Rsa: nan
  
  ## 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: 1e-05
  - train_batch_size: 20
  - eval_batch_size: 8
  - seed: 1996
  - 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 | Rmse   | Rmse Cause::a Causata da un essere umano | Mae    | Mae Cause::a Causata da un essere umano | R2     | R2 Cause::a Causata da un essere umano | Cos    | Pair | Rank | Neighbors | Rsa |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:----------------------------------------:|:------:|:---------------------------------------:|:------:|:--------------------------------------:|:------:|:----:|:----:|:---------:|:---:|
  | 1.0874        | 1.0   | 15   | 1.2615          | 1.6296 | 1.6296                                   | 1.3836 | 1.3836                                  | 0.0393 | 0.0393                                 | 0.0435 | 0.0  | 0.5  | 0.2935    | nan |
  | 0.9577        | 2.0   | 30   | 1.1988          | 1.5886 | 1.5886                                   | 1.3017 | 1.3017                                  | 0.0870 | 0.0870                                 | 0.4783 | 0.0  | 0.5  | 0.3944    | nan |
  | 0.8414        | 3.0   | 45   | 0.9870          | 1.4414 | 1.4414                                   | 1.1963 | 1.1963                                  | 0.2483 | 0.2483                                 | 0.3913 | 0.0  | 0.5  | 0.3048    | nan |
  | 0.7291        | 4.0   | 60   | 0.9098          | 1.3839 | 1.3839                                   | 1.1297 | 1.1297                                  | 0.3071 | 0.3071                                 | 0.4783 | 0.0  | 0.5  | 0.3084    | nan |
  | 0.5949        | 5.0   | 75   | 0.9207          | 1.3921 | 1.3921                                   | 1.2079 | 1.2079                                  | 0.2988 | 0.2988                                 | 0.4783 | 0.0  | 0.5  | 0.3084    | nan |
  | 0.4938        | 6.0   | 90   | 0.8591          | 1.3448 | 1.3448                                   | 1.1842 | 1.1842                                  | 0.3458 | 0.3458                                 | 0.4783 | 0.0  | 0.5  | 0.3084    | nan |
  | 0.3611        | 7.0   | 105  | 0.8176          | 1.3119 | 1.3119                                   | 1.1454 | 1.1454                                  | 0.3774 | 0.3774                                 | 0.5652 | 0.0  | 0.5  | 0.4091    | nan |
  | 0.2663        | 8.0   | 120  | 0.6879          | 1.2034 | 1.2034                                   | 1.0300 | 1.0300                                  | 0.4761 | 0.4761                                 | 0.5652 | 0.0  | 0.5  | 0.4091    | nan |
  | 0.1833        | 9.0   | 135  | 0.7704          | 1.2735 | 1.2735                                   | 1.1031 | 1.1031                                  | 0.4133 | 0.4133                                 | 0.5652 | 0.0  | 0.5  | 0.3152    | nan |
  | 0.1704        | 10.0  | 150  | 0.7097          | 1.2222 | 1.2222                                   | 1.0382 | 1.0382                                  | 0.4596 | 0.4596                                 | 0.4783 | 0.0  | 0.5  | 0.3084    | nan |
  | 0.1219        | 11.0  | 165  | 0.6872          | 1.2027 | 1.2027                                   | 1.0198 | 1.0198                                  | 0.4767 | 0.4767                                 | 0.4783 | 0.0  | 0.5  | 0.3084    | nan |
  | 0.1011        | 12.0  | 180  | 0.7201          | 1.2312 | 1.2312                                   | 1.0466 | 1.0466                                  | 0.4516 | 0.4516                                 | 0.5652 | 0.0  | 0.5  | 0.3152    | nan |
  | 0.0849        | 13.0  | 195  | 0.7267          | 1.2368 | 1.2368                                   | 1.0454 | 1.0454                                  | 0.4466 | 0.4466                                 | 0.4783 | 0.0  | 0.5  | 0.3953    | nan |
  | 0.08