readme: ---
  license: mit
  tags:
  - generated_from_trainer
  model-index:
  - name: predict-perception-bert-cause-concept
    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-concept
  
  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: 0.4044
  - Rmse: 0.6076
  - Rmse Cause::a Causata da un concetto astratto (es. gelosia): 0.6076
  - Mae: 0.4548
  - Mae Cause::a Causata da un concetto astratto (es. gelosia): 0.4548
  - R2: 0.5463
  - R2 Cause::a Causata da un concetto astratto (es. gelosia): 0.5463
  - Cos: 0.2174
  - Pair: 0.0
  - Rank: 0.5
  - Neighbors: 0.3931
  - 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 concetto astratto (es. gelosia) | Mae    | Mae Cause::a Causata da un concetto astratto (es. gelosia) | R2      | R2 Cause::a Causata da un concetto astratto (es. gelosia) | Cos    | Pair | Rank | Neighbors | Rsa |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:-----------------------------------------------------------:|:------:|:----------------------------------------------------------:|:-------:|:---------------------------------------------------------:|:------:|:----:|:----:|:---------:|:---:|
  | 1.08          | 1.0   | 15   | 0.9520          | 0.9323 | 0.9323                                                      | 0.6560 | 0.6560                                                     | -0.0680 | -0.0680                                                   | 0.0435 | 0.0  | 0.5  | 0.3188    | nan |
  | 0.9974        | 2.0   | 30   | 0.8621          | 0.8872 | 0.8872                                                      | 0.5962 | 0.5962                                                     | 0.0328  | 0.0328                                                    | 0.1304 | 0.0  | 0.5  | 0.4066    | nan |
  | 0.9337        | 3.0   | 45   | 0.9223          | 0.9176 | 0.9176                                                      | 0.6608 | 0.6608                                                     | -0.0347 | -0.0347                                                   | 0.2174 | 0.0  | 0.5  | 0.3632    | nan |
  | 0.966         | 4.0   | 60   | 0.8273          | 0.8691 | 0.8691                                                      | 0.5874 | 0.5874                                                     | 0.0719  | 0.0719                                                    | 0.2174 | 0.0  | 0.5  | 0.3754    | nan |
  | 0.8683        | 5.0   | 75   | 0.8741          | 0.8933 | 0.8933                                                      | 0.6136 | 0.6136                                                     | 0.0193  | 0.0193                                                    | 0.2174 | 0.0  | 0.5  | 0.3529    | nan |
  | 0.8522        | 6.0   | 90   | 0.7781          | 0.8428 | 0.8428                                                      | 0.5732 | 0.5732                                                     | 0.1271  | 0.1271                                                    | 0.2174 | 0.0  | 0.5  | 0.4152    | nan |
  | 0.7968        | 7.0   | 105  | 0.7257          | 0.8139 | 0.8139                                                      | 0.5519 | 0.5519                                                     | 0.1859  | 0.1859                                                    | 0.2174 | 0.0  | 0.5  | 0.4152    | nan |
  | 0.7166        | 8.0   | 120  | 0.7122          | 0.8064 | 0.8064                                                      | 0.5792 | 0.5792                                                     | 0.2010  | 0.2010                                                    | 0.1304 | 0.0  | 0.5  | 0.3955    | nan |
  | 0.6246        | 9.0   | 135  | 0.6771          | 0.7862 | 0.7862                                                      | 0.5701 | 0.5701                                                     | 0.2403  | 0.2403                                                    | 0.0435 | 0.0  | 0.5  | 0.3955    | nan |
  | 0.5205        | 10.0  | 150  | 0.6704          | 0.7823 | 0.7823                                                      | 0.5735 | 0.5735                                                     | 0.2479  | 0.2479                                                    | 0.3913 | 0.0  | 0.5  | 0.