LABEL_0
---
license: mit
tags:
- generated_from_trainer
model-index:
- name: predict-perception-bert-cause-none
  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-none

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: 1.6269
- Rmse: 1.2763
- Rmse Cause::a Spontanea, priva di un agente scatenante: 1.2763
- Mae: 1.0431
- Mae Cause::a Spontanea, priva di un agente scatenante: 1.0431
- R2: -1.4329
- R2 Cause::a Spontanea, priva di un agente scatenante: -1.4329
- Cos: -0.3913
- Pair: 0.0
- Rank: 0.5
- Neighbors: 0.3371
- 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 Spontanea, priva di un agente scatenante | Mae    | Mae Cause::a Spontanea, priva di un agente scatenante | R2      | R2 Cause::a Spontanea, priva di un agente scatenante | Cos     | Pair | Rank | Neighbors | Rsa |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------------------------------------------------------:|:------:|:-----------------------------------------------------:|:-------:|:----------------------------------------------------:|:-------:|:----:|:----:|:---------:|:---:|
| 0.994         | 1.0   | 15   | 0.7156          | 0.8465 | 0.8465                                                 | 0.7809 | 0.7809                                                | -0.0701 | -0.0701                                              | -0.1304 | 0.0  | 0.5  | 0.2971    | nan |
| 0.9757        | 2.0   | 30   | 0.7096          | 0.8429 | 0.8429                                                 | 0.7666 | 0.7666                                                | -0.0611 | -0.0611                                              | 0.0435  | 0.0  | 0.5  | 0.2515    | nan |
| 1.0086        | 3.0   | 45   | 0.7779          | 0.8825 | 0.8825                                                 | 0.7981 | 0.7981                                                | -0.1632 | -0.1632                                              | -0.0435 | 0.0  | 0.5  | 0.2899    | nan |
| 0.9127        | 4.0   | 60   | 0.8158          | 0.9038 | 0.9038                                                 | 0.8171 | 0.8171                                                | -0.2199 | -0.2199                                              | -0.2174 | 0.0  | 0.5  | 0.2975    | nan |
| 0.8555        | 5.0   | 75   | 0.7691          | 0.8775 | 0.8775                                                 | 0.8121 | 0.8121                                                | -0.1501 | -0.1501                                              | -0.2174 | 0.0  | 0.5  | 0.3299    | nan |
| 0.8702        | 6.0   | 90   | 0.7818          | 0.8848 | 0.8848                                                 | 0.7781 | 0.7781                                                | -0.1691 | -0.1691                                              | 0.0435  | 0.0  | 0.5  | 0.2515    | nan |
| 0.76          | 7.0   | 105  | 0.8377          | 0.9158 | 0.9158                                                 | 0.7985 | 0.7985                                                | -0.2526 | -0.2526                                              | 0.0435  | 0.0  | 0.5  | 0.2515    | nan |
| 0.6997        | 8.0   | 120  | 0.9065          | 0.9527 | 0.9527                                                 | 0.8370 | 0.8370                                                | -0.3555 | -0.3555                                              | -0.2174 | 0.0  | 0.5  | 0.3147    | nan |
| 0.5963        | 9.0   | 135  | 1.0611          | 1.0308 | 1.0308                                                 | 0.8396 | 0.8396                                                | -0.5867 | -0.5867                                              | -0.0435 | 0.0  | 0.5  | 0.2645    | nan |
| 0.5413        | 10.0  | 150  | 1.1724          | 1.0835 | 1.0835                                                 | 0.8649 | 0.8649                                                | -0.7532 | -0.7532                                              | -0.0435 | 0.0  | 0.5  | 0.2645    | nan |
| 0.4994        | 11.0  | 165  | 1.1471          | 1.0717 | 1.0717                                                 | 0.8857 | 0.8857                                                | -0.7154 | -0.7154                                              | -0.2174 | 0.0  | 0.5  | 0.3271    | nan |
| 0.4208        | 12.0  | 180  | 1.2136          | 1.1024 | 1.1024                                                 | 0.9392 | 0.9392                                                | -0.8148 | -0.8148                                              | -0.2174 | 0.0  | 0.5  | 0.3169    | nan |
| 0.316         | 13.0  | 195  | 1.3499          | 1.1626 | 1.1626                                                 | 0.9395 | 0.9395                                                | -1.0187 | -1.0187                                              | -0.2174 | 0.0  | 0.5  | 0.3271    | nan |
| 0.2893        | 14.0  | 210  | 1.4229          | 1.1937 | 1.1937                                                 | 0.9608 | 0.9608                                                | -1.1278 | -1.1278                                              | -0.3043 | 0.0  | 0.5  | 0.3269    | nan |
| 0.235         | 15.0  | 225  | 1.4699          | 1.2132 | 1.2132                                                 | 0.9785 | 0.9785                                                | -1.1981 | -1.1981                                              | -0.0435 | 0.0  | 0.5  | 0.2865    | nan |
| 0.2397        | 16.0  | 240  | 1.5492          | 1.2455 | 1.2455                                                 | 1.0005 | 1.0005                                                | -1.3167 | -1.3167                                              | -0.0435 | 0.0  | 0.5  | 0.2655    | nan |
| 0.1973        | 17.0  | 255  | 1.5541          | 1.2474 | 1.2474                                                 | 1.0165 | 1.0165                                                | -1.3239 | -1.3239                                              | -0.0435 | 0.0  | 0.5  | 0.2655    | nan |
| 0.1793        | 18.0  | 270  | 1.4966          | 1.2242 | 1.2242                                                 | 1.0058 | 1.0058                                                | -1.2380 | -1.2380                                              | -0.3043 | 0.0  | 0.5  | 0.3437    | nan |
| 0.16          | 19.0  | 285  | 1.4977          | 1.2246 | 1.2246                                                 | 1.0140 | 1.0140                                                | -1.2396 | -1.2396                                              | -0.3913 | 0.0  | 0.5  | 0.3371    | nan |
| 0.1501        | 20.0  | 300  | 1.5751          | 1.2558 | 1.2558                                                 | 1.0254 | 1.0254                                                | -1.3553 | -1.3553                                              | -0.3913 | 0.0  | 0.5  | 0.3371    | nan |
| 0.1342        | 21.0  | 315  | 1.7011          | 1.3051 | 1.3051                                                 | 1.0681 | 1.0681                                                | -1.5438 | -1.5438                                              | -0.2174 | 0.0  | 0.5  | 0.2715    | nan |
| 0.137         | 22.0  | 330  | 1.5557          | 1.2481 | 1.2481                                                 | 1.0393 | 1.0393                                                | -1.3263 | -1.3263                                              | -0.3043 | 0.0  | 0.5  | 0.3437    | nan |
| 0.11          | 23.0  | 345  | 1.5475          | 1.2448 | 1.2448                                                 | 1.0320 | 1.0320                                                | -1.3141 | -1.3141                                              | -0.3913 | 0.0  | 0.5  | 0.3371    | nan |
| 0.1106        | 24.0  | 360  | 1.6006          | 1.2660 | 1.2660                                                 | 1.0452 | 1.0452                                                | -1.3936 | -1.3936                                              | -0.3913 | 0.0  | 0.5  | 0.3297    | nan |
| 0.1013        | 25.0  | 375  | 1.5907          | 1.2621 | 1.2621                                                 | 1.0368 | 1.0368                                                | -1.3787 | -1.3787                                              | -0.3043 | 0.0  | 0.5  | 0.2929    | nan |
| 0.0863        | 26.0  | 390  | 1.6436          | 1.2829 | 1.2829                                                 | 1.0496 | 1.0496                                                | -1.4578 | -1.4578                                              | -0.3043 | 0.0  | 0.5  | 0.2929    | nan |
| 0.0929        | 27.0  | 405  | 1.6000          | 1.2658 | 1.2658                                                 | 1.0341 | 1.0341                                                | -1.3927 | -1.3927                                              | -0.3043 | 0.0  | 0.5  | 0.3245    | nan |
| 0.0829        | 28.0  | 420  | 1.6277          | 1.2767 | 1.2767                                                 | 1.0422 | 1.0422                                                | -1.4341 | -1.4341                                              | -0.3913 | 0.0  | 0.5  | 0.3371    | nan |
| 0.0884        | 29.0  | 435  | 1.6324          | 1.2785 | 1.2785                                                 | 1.0436 | 1.0436                                                | -1.4411 | -1.4411                                              | -0.3913 | 0.0  | 0.5  | 0.3371    | nan |
| 0.0896        | 30.0  | 450  | 1.6269          | 1.2763 | 1.2763                                                 | 1.0431 | 1.0431                                                | -1.4329 | -1.4329                                              | -0.3913 | 0.0  | 0.5  | 0.3371    | nan |


### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.2+cu113
- Datasets 1.18.3
- Tokenizers 0.11.0
