readme: ---
  license: mit
  tags:
  - generated_from_trainer
  model-index:
  - name: predict-perception-bert-blame-victim
    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-blame-victim
  
  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: 0.5075
  - Rmse: 0.4599
  - Rmse Blame::a La vittima: 0.4599
  - Mae: 0.3607
  - Mae Blame::a La vittima: 0.3607
  - R2: -0.1848
  - R2 Blame::a La vittima: -0.1848
  - Cos: 0.2174
  - Pair: 0.0
  - Rank: 0.5
  - Neighbors: 0.2924
  - 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 Blame::a La vittima | Mae    | Mae Blame::a La vittima | R2      | R2 Blame::a La vittima | Cos     | Pair | Rank | Neighbors | Rsa |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------------------------:|:------:|:-----------------------:|:-------:|:----------------------:|:-------:|:----:|:----:|:---------:|:---:|
  | 1.0264        | 1.0   | 15   | 0.4334          | 0.4250 | 0.4250                   | 0.3666 | 0.3666                  | -0.0119 | -0.0119                | 0.1304  | 0.0  | 0.5  | 0.2703    | nan |
  | 0.9814        | 2.0   | 30   | 0.4505          | 0.4333 | 0.4333                   | 0.3744 | 0.3744                  | -0.0517 | -0.0517                | 0.2174  | 0.0  | 0.5  | 0.2751    | nan |
  | 0.9283        | 3.0   | 45   | 0.4349          | 0.4257 | 0.4257                   | 0.3627 | 0.3627                  | -0.0152 | -0.0152                | 0.1304  | 0.0  | 0.5  | 0.2779    | nan |
  | 0.8904        | 4.0   | 60   | 0.4662          | 0.4408 | 0.4408                   | 0.3773 | 0.3773                  | -0.0884 | -0.0884                | -0.0435 | 0.0  | 0.5  | 0.2681    | nan |
  | 0.836         | 5.0   | 75   | 0.4188          | 0.4177 | 0.4177                   | 0.3609 | 0.3609                  | 0.0223  | 0.0223                 | 0.2174  | 0.0  | 0.5  | 0.3051    | nan |
  | 0.8293        | 6.0   | 90   | 0.4142          | 0.4155 | 0.4155                   | 0.3512 | 0.3512                  | 0.0330  | 0.0330                 | 0.2174  | 0.0  | 0.5  | 0.3220    | nan |
  | 0.7629        | 7.0   | 105  | 0.3837          | 0.3999 | 0.3999                   | 0.3387 | 0.3387                  | 0.1041  | 0.1041                 | 0.2174  | 0.0  | 0.5  | 0.3051    | nan |
  | 0.7266        | 8.0   | 120  | 0.3664          | 0.3907 | 0.3907                   | 0.3250 | 0.3250                  | 0.1446  | 0.1446                 | 0.3043  | 0.0  | 0.5  | 0.3409    | nan |
  | 0.6121        | 9.0   | 135  | 0.3718          | 0.3936 | 0.3936                   | 0.3312 | 0.3312                  | 0.1320  | 0.1320                 | 0.3043  | 0.0  | 0.5  | 0.3983    | nan |
  | 0.5694        | 10.0  | 150  | 0.3679          | 0.3915 | 0.3915                   | 0.3197 | 0.3197                  | 0.1411  | 0.1411                 | 0.3913  | 0.0  | 0.5  | 0.3518    | nan |
  | 0.4647        | 11.0  | 165  | 0.3868          | 0.4015 | 0.4015                   | 0.3340 | 0.3340                  | 0.0970  | 0.0970                 | 0.2174  | 0.0  | 0.5  | 0.3285    | nan |
  | 0.4212        | 12.0  | 180  | 0.3717          | 0.3936 | 0.3936                   | 0.3188 | 0.3188                  | 0.1322  | 0.1322                 | 0.3913  | 0.0  | 0.5  | 0.3518    | nan |
  | 0.3605        | 13.0  | 195  | 0.3437          | 0.3784 | 0.3784                   | 0.3066 | 0.3066                  | 0.1976  | 0.1976                 | 0.3043  | 0.0  | 0.5  | 0.3423    | nan |
  | 0.2759        | 14.0  | 210  | 0.3892          | 0.4027 | 0.4027                   | 0.3230 | 0.3230                  | 0.0914  | 0.0914                 | 0.3913  | 0.0  | 0.5  | 0.3518    | nan |
  | 0.2868        | 15.0  | 225  | 0.3720          | 0.3937 | 0.3937                   | 0.3218 | 0.3218                  | 0.1315  | 0.1315                 | 0.3913  | 0.0  | 0.5  | 0.3440    | nan |
  | 0.2467        | 16.0  | 240  | 0.3881          | 0.4022 | 0.4022                   | 0.3291 | 0.3291                  | 0.0939  | 0.0939                 | 0.3043  | 0.0  | 0.5  | 0.3363    | nan |
  | 0.2013        | 17.0  | 255  | 0.4121          | 0.4144 | 0.4144                   | 0.3373 | 0.3373                  | 0.0380  | 0.0380     