readme: ---
  license: mit
  tags:
  - generated_from_trainer
  model-index:
  - name: predict-perception-xlmr-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-xlmr-cause-human
  
  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7632
  - Rmse: 1.2675
  - Rmse Cause::a Causata da un essere umano: 1.2675
  - Mae: 0.9299
  - Mae Cause::a Causata da un essere umano: 0.9299
  - R2: 0.4188
  - R2 Cause::a Causata da un essere umano: 0.4188
  - Cos: 0.3913
  - Pair: 0.0
  - Rank: 0.5
  - Neighbors: 0.4082
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:----------------------------------------:|:------:|:---------------------------------------:|:-------:|:--------------------------------------:|:-------:|:----:|:----:|:---------:|:---:|
  | 1.0174        | 1.0   | 15   | 1.3796          | 1.7041 | 1.7041                                   | 1.3614 | 1.3614                                  | -0.0506 | -0.0506                                | -0.1304 | 0.0  | 0.5  | 0.2971    | nan |
  | 0.9534        | 2.0   | 30   | 1.1173          | 1.5336 | 1.5336                                   | 1.2624 | 1.2624                                  | 0.1491  | 0.1491                                 | 0.4783  | 0.0  | 0.5  | 0.4446    | nan |
  | 0.8883        | 3.0   | 45   | 1.0580          | 1.4923 | 1.4923                                   | 1.2451 | 1.2451                                  | 0.1943  | 0.1943                                 | 0.5652  | 0.0  | 0.5  | 0.4957    | nan |
  | 0.8215        | 4.0   | 60   | 1.0200          | 1.4653 | 1.4653                                   | 1.2087 | 1.2087                                  | 0.2232  | 0.2232                                 | 0.6522  | 0.0  | 0.5  | 0.5123    | nan |
  | 0.744         | 5.0   | 75   | 1.1496          | 1.5556 | 1.5556                                   | 1.2573 | 1.2573                                  | 0.1245  | 0.1245                                 | 0.2174  | 0.0  | 0.5  | 0.3007    | nan |
  | 0.7056        | 6.0   | 90   | 0.9641          | 1.4246 | 1.4246                                   | 1.1763 | 1.1763                                  | 0.2658  | 0.2658                                 | 0.4783  | 0.0  | 0.5  | 0.3619    | nan |
  | 0.6136        | 7.0   | 105  | 0.8328          | 1.3240 | 1.3240                                   | 1.0948 | 1.0948                                  | 0.3658  | 0.3658                                 | 0.4783  | 0.0  | 0.5  | 0.3628    | nan |
  | 0.5185        | 8.0   | 120  | 0.6890          | 1.2043 | 1.2043                                   | 1.0112 | 1.0112                                  | 0.4753  | 0.4753                                 | 0.3913  | 0.0  | 0.5  | 0.4082    | nan |
  | 0.5029        | 9.0   | 135  | 1.0380          | 1.4782 | 1.4782                                   | 1.1215 | 1.1215                                  | 0.2095  | 0.2095                                 | 0.3913  | 0.0  | 0.5  | 0.3781    | nan |
  | 0.4624        | 10.0  | 150  | 1.1780          | 1.5747 | 1.5747                                   | 1.2852 | 1.2852                                  | 0.1029  | 0.1029                                 | 0.3913  | 0.0  | 0.5  | 0.4082    | nan |
  | 0.4098        | 11.0  | 165  | 0.8714          | 1.3544 | 1.3544                                   | 1.1388 | 1.1388                                  | 0.3364  | 0.3364                                 | 0.3913  | 0.0  | 0.5  | 0.4082    | nan |
  | 0.348         | 12.0  | 180  | 0.7260          | 1.2362 | 1.2362                                   | 0.9563 | 0.9563                                  | 0.4471  | 0.4471                                 | 0.5652  | 0.0  | 0.5  | 0.4957    | nan |
  | 0.3437        | 13.0  | 195  | 0.7241          | 1.2346 | 1.2346                                   | 0.8998 | 0.8998                                  | 0.4485  | 0.4485                                 | 0.6522  | 0.0  | 0.5  | 0.4727    | nan |
  | 0.2727  