pytorch tensorboard xlm-roberta text-classification transformers generated_from_trainer license:mit model-index
---
license: mit
tags:
- generated_from_trainer
model-index:
- name: predict-perception-xlmr-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-xlmr-cause-none

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: 1.8639
- Rmse: 1.3661
- Rmse Cause::a Spontanea, priva di un agente scatenante: 1.3661
- Mae: 1.0795
- Mae Cause::a Spontanea, priva di un agente scatenante: 1.0795
- R2: -1.7872
- R2 Cause::a Spontanea, priva di un agente scatenante: -1.7872
- Cos: -0.3043
- Pair: 0.0
- Rank: 0.5
- Neighbors: 0.3501
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------------------------------------------------------:|:------:|:-----------------------------------------------------:|:-------:|:----------------------------------------------------:|:-------:|:----:|:----:|:---------:|:---:|
| 1.0626        | 1.0   | 15   | 0.6787          | 0.8244 | 0.8244                                                 | 0.7453 | 0.7453                                                | -0.0149 | -0.0149                                              | 0.0435  | 0.0  | 0.5  | 0.2515    | nan |
| 1.0186        | 2.0   | 30   | 0.6769          | 0.8233 | 0.8233                                                 | 0.7457 | 0.7457                                                | -0.0122 | -0.0122                                              | 0.0435  | 0.0  | 0.5  | 0.2515    | nan |
| 1.0346        | 3.0   | 45   | 0.6812          | 0.8259 | 0.8259                                                 | 0.7489 | 0.7489                                                | -0.0187 | -0.0187                                              | 0.0435  | 0.0  | 0.5  | 0.2515    | nan |
| 0.9481        | 4.0   | 60   | 1.0027          | 1.0020 | 1.0020                                                 | 0.8546 | 0.8546                                                | -0.4994 | -0.4994                                              | -0.3043 | 0.0  | 0.5  | 0.2579    | nan |
| 0.8838        | 5.0   | 75   | 0.9352          | 0.9677 | 0.9677                                                 | 0.8463 | 0.8463                                                | -0.3985 | -0.3985                                              | -0.2174 | 0.0  | 0.5  | 0.2966    | nan |
| 0.7971        | 6.0   | 90   | 0.9396          | 0.9700 | 0.9700                                                 | 0.8608 | 0.8608                                                | -0.4050 | -0.4050                                              | -0.2174 | 0.0  | 0.5  | 0.3156    | nan |
| 0.8182        | 7.0   | 105  | 0.9485          | 0.9746 | 0.9746                                                 | 0.8509 | 0.8509                                                | -0.4184 | -0.4184                                              | -0.1304 | 0.0  | 0.5  | 0.2788    | nan |
| 0.696         | 8.0   | 120  | 1.1396          | 1.0682 | 1.0682                                                 | 0.9309 | 0.9309                                                | -0.7041 | -0.7041                                              | -0.1304 | 0.0  | 0.5  | 0.2899    | nan |
| 0.6337        | 9.0   | 135  | 1.3064          | 1.1437 | 1.1437                                                 | 0.9612 | 0.9612                                                | -0.9536 | -0.9536                                              | -0.3913 | 0.0  | 0.5  | 0.4018    | nan |
| 0.5308        | 10.0  | 150  | 1.2403          | 1.1144 | 1.1144                                                 | 0.9359 | 0.9359                                                | -0.8547 | -0.8547                                              | -0.3913 | 0.0  | 0.5  | 0.4018    | nan |
| 0.5226        | 11.0  | 165  | 1.3433          | 1.1597 | 1.1597                                                 | 0.9542 | 0.9542                                                | -1.0087 | -1.0087                                              | -0.3913 | 0.0  | 0.5  | 0.4018    | nan |
| 0.474         | 12.0  | 180  | 1.5321          | 1.2386 | 1.2386                                                 | 1.0340 | 1.0340                                                | -1.2910 | -1.2910                                              | -0.3043 | 0.0  | 0.5  | 0.3205    | nan |
| 0.3899        | 13.0  | 195  | 1.6322          | 1.2784 | 1.2784                                                 | 1.0083 | 1.0083                                                | -1.4408 | -1.4408                                              | -0.3043 | 0.0  | 0.5  | 0.3590    | nan |
| 0.3937        | 14.0  | 210  | 1.7519          | 1.3244 | 1.3244                                                 | 1.0540 | 1.0540                                                | -1.6197 | -1.6197                                              | -0.3913 | 0.0  | 0.5  | 0.4018    | nan |
| 0.4128        | 15.0  | 225  | 1.8588          | 1.3643 | 1.3643                                                 | 1.0765 | 1.0765                                                | -1.7797 | -1.7797                                              | -0.3913 | 0.0  | 0.5  | 0.4018    | nan |
| 0.3424        | 16.0  | 240  | 1.7211          | 1.3128 | 1.3128                                                 | 1.0217 | 1.0217                                                | -1.5737 | -1.5737                                              | -0.3913 | 0.0  | 0.5  | 0.4018    | nan |
| 0.3307        | 17.0  | 255  | 1.7802          | 1.3351 | 1.3351                                                 | 1.0790 | 1.0790                                                | -1.6621 | -1.6621                                              | -0.3043 | 0.0  | 0.5  | 0.3205    | nan |
| 0.2972        | 18.0  | 270  | 1.5272          | 1.2366 | 1.2366                                                 | 0.9945 | 0.9945                                                | -1.2837 | -1.2837                                              | -0.3043 | 0.0  | 0.5  | 0.3501    | nan |
| 0.2862        | 19.0  | 285  | 1.7213          | 1.3128 | 1.3128                                                 | 1.0574 | 1.0574                                                | -1.5740 | -1.5740                                              | -0.3913 | 0.0  | 0.5  | 0.3815    | nan |
| 0.2844        | 20.0  | 300  | 1.8999          | 1.3793 | 1.3793                                                 | 1.0930 | 1.0930                                                | -1.8411 | -1.8411                                              | -0.3043 | 0.0  | 0.5  | 0.3501    | nan |
| 0.2404        | 21.0  | 315  | 1.9806          | 1.4082 | 1.4082                                                 | 1.1221 | 1.1221                                                | -1.9617 | -1.9617                                              | -0.3913 | 0.0  | 0.5  | 0.3815    | nan |
| 0.2349        | 22.0  | 330  | 1.8649          | 1.3665 | 1.3665                                                 | 1.0953 | 1.0953                                                | -1.7888 | -1.7888                                              | -0.3913 | 0.0  | 0.5  | 0.3815    | nan |
| 0.2323        | 23.0  | 345  | 1.8256          | 1.3520 | 1.3520                                                 | 1.0694 | 1.0694                                                | -1.7299 | -1.7299                                              | -0.3913 | 0.0  | 0.5  | 0.4018    | nan |
| 0.2217        | 24.0  | 360  | 1.9150          | 1.3847 | 1.3847                                                 | 1.1017 | 1.1017                                                | -1.8636 | -1.8636                                              | -0.3043 | 0.0  | 0.5  | 0.3501    | nan |
| 0.2262        | 25.0  | 375  | 1.8536          | 1.3624 | 1.3624                                                 | 1.0667 | 1.0667                                                | -1.7719 | -1.7719                                              | -0.3043 | 0.0  | 0.5  | 0.3501    | nan |
| 0.2052        | 26.0  | 390  | 1.7727          | 1.3323 | 1.3323                                                 | 1.0475 | 1.0475                                                | -1.6508 | -1.6508                                              | -0.3043 | 0.0  | 0.5  | 0.3501    | nan |
| 0.2121        | 27.0  | 405  | 1.8088          | 1.3458 | 1.3458                                                 | 1.0588 | 1.0588                                                | -1.7048 | -1.7048                                              | -0.3043 | 0.0  | 0.5  | 0.3501    | nan |
| 0.1723        | 28.0  | 420  | 1.8283          | 1.3530 | 1.3530                                                 | 1.0628 | 1.0628                                                | -1.7340 | -1.7340                                              | -0.3043 | 0.0  | 0.5  | 0.3501    | nan |
| 0.1932        | 29.0  | 435  | 1.8566          | 1.3635 | 1.3635                                                 | 1.0763 | 1.0763                                                | -1.7764 | -1.7764                                              | -0.3043 | 0.0  | 0.5  | 0.3501    | nan |
| 0.2157        | 30.0  | 450  | 1.8639          | 1.3661 | 1.3661                                                 | 1.0795 | 1.0795                                                | -1.7872 | -1.7872                                              | -0.3043 | 0.0  | 0.5  | 0.3501    | nan |


### Framework versions

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