LABEL_0
---
license: mit
tags:
- generated_from_trainer
model-index:
- name: predict-perception-xlmr-focus-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-xlmr-focus-concept

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: 0.8296
- Rmse: 1.0302
- Rmse Focus::a Su un concetto astratto o un'emozione: 1.0302
- Mae: 0.7515
- Mae Focus::a Su un concetto astratto o un'emozione: 0.7515
- R2: 0.1804
- R2 Focus::a Su un concetto astratto o un'emozione: 0.1804
- Cos: 0.4783
- Pair: 0.0
- Rank: 0.5
- Neighbors: 0.3415
- 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 Focus::a Su un concetto astratto o un'emozione | Mae    | Mae Focus::a Su un concetto astratto o un'emozione | R2      | R2 Focus::a Su un concetto astratto o un'emozione | Cos    | Pair | Rank | Neighbors | Rsa |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------------------------------------------------:|:------:|:--------------------------------------------------:|:-------:|:-------------------------------------------------:|:------:|:----:|:----:|:---------:|:---:|
| 1.0355        | 1.0   | 15   | 0.9822          | 1.1209 | 1.1209                                              | 0.9649 | 0.9649                                             | 0.0296  | 0.0296                                            | 0.2174 | 0.0  | 0.5  | 0.3706    | nan |
| 1.0083        | 2.0   | 30   | 1.1378          | 1.2065 | 1.2065                                              | 0.9954 | 0.9954                                             | -0.1241 | -0.1241                                           | 0.2174 | 0.0  | 0.5  | 0.3309    | nan |
| 0.9823        | 3.0   | 45   | 0.9669          | 1.1121 | 1.1121                                              | 0.9315 | 0.9315                                             | 0.0448  | 0.0448                                            | 0.3043 | 0.0  | 0.5  | 0.3810    | nan |
| 0.9468        | 4.0   | 60   | 0.8856          | 1.0644 | 1.0644                                              | 0.8584 | 0.8584                                             | 0.1251  | 0.1251                                            | 0.3913 | 0.0  | 0.5  | 0.3803    | nan |
| 0.9294        | 5.0   | 75   | 0.8136          | 1.0202 | 1.0202                                              | 0.8396 | 0.8396                                             | 0.1963  | 0.1963                                            | 0.6522 | 0.0  | 0.5  | 0.4727    | nan |
| 0.881         | 6.0   | 90   | 0.7634          | 0.9882 | 0.9882                                              | 0.8192 | 0.8192                                             | 0.2458  | 0.2458                                            | 0.6522 | 0.0  | 0.5  | 0.4727    | nan |
| 0.7589        | 7.0   | 105  | 0.8139          | 1.0204 | 1.0204                                              | 0.8136 | 0.8136                                             | 0.1960  | 0.1960                                            | 0.5652 | 0.0  | 0.5  | 0.4120    | nan |
| 0.7217        | 8.0   | 120  | 0.9105          | 1.0792 | 1.0792                                              | 0.9394 | 0.9394                                             | 0.1005  | 0.1005                                            | 0.3913 | 0.0  | 0.5  | 0.4108    | nan |
| 0.8059        | 9.0   | 135  | 1.0322          | 1.1491 | 1.1491                                              | 0.9115 | 0.9115                                             | -0.0197 | -0.0197                                           | 0.5652 | 0.0  | 0.5  | 0.3738    | nan |
| 0.6483        | 10.0  | 150  | 0.7989          | 1.0109 | 1.0109                                              | 0.7899 | 0.7899                                             | 0.2108  | 0.2108                                            | 0.6522 | 0.0  | 0.5  | 0.4727    | nan |
| 0.5725        | 11.0  | 165  | 0.7175          | 0.9581 | 0.9581                                              | 0.7011 | 0.7011                                             | 0.2912  | 0.2912                                            | 0.5652 | 0.0  | 0.5  | 0.3738    | nan |
| 0.5091        | 12.0  | 180  | 0.8818          | 1.0621 | 1.0621                                              | 0.8775 | 0.8775                                             | 0.1289  | 0.1289                                            | 0.5652 | 0.0  | 0.5  | 0.4063    | nan |
| 0.4526        | 13.0  | 195  | 0.8451          | 1.0398 | 1.0398                                              | 0.7990 | 0.7990                                             | 0.1651  | 0.1651                                            | 0.5652 | 0.0  | 0.5  | 0.4063    | nan |
| 0.361         | 14.0  | 210  | 0.8632          | 1.0508 | 1.0508                                              | 0.8124 | 0.8124                                             | 0.1472  | 0.1472                                            | 0.4783 | 0.0  | 0.5  | 0.3699    | nan |
| 0.3582        | 15.0  | 225  | 0.8461          | 1.0404 | 1.0404                                              | 0.7923 | 0.7923                                             | 0.1641  | 0.1641                                            | 0.3913 | 0.0  | 0.5  | 0.3672    | nan |
| 0.2945        | 16.0  | 240  | 0.9142          | 1.0814 | 1.0814                                              | 0.8125 | 0.8125                                             | 0.0968  | 0.0968                                            | 0.3913 | 0.0  | 0.5  | 0.3672    | nan |
| 0.2891        | 17.0  | 255  | 0.8377          | 1.0352 | 1.0352                                              | 0.7718 | 0.7718                                             | 0.1724  | 0.1724                                            | 0.4783 | 0.0  | 0.5  | 0.3415    | nan |
| 0.2569        | 18.0  | 270  | 0.8106          | 1.0183 | 1.0183                                              | 0.7481 | 0.7481                                             | 0.1992  | 0.1992                                            | 0.4783 | 0.0  | 0.5  | 0.3415    | nan |
| 0.2583        | 19.0  | 285  | 0.8239          | 1.0266 | 1.0266                                              | 0.7597 | 0.7597                                             | 0.1861  | 0.1861                                            | 0.4783 | 0.0  | 0.5  | 0.3415    | nan |
| 0.2217        | 20.0  | 300  | 0.8485          | 1.0419 | 1.0419                                              | 0.7663 | 0.7663                                             | 0.1617  | 0.1617                                            | 0.4783 | 0.0  | 0.5  | 0.3415    | nan |
| 0.1927        | 21.0  | 315  | 0.8304          | 1.0307 | 1.0307                                              | 0.7536 | 0.7536                                             | 0.1797  | 0.1797                                            | 0.4783 | 0.0  | 0.5  | 0.3415    | nan |
| 0.176         | 22.0  | 330  | 0.8321          | 1.0317 | 1.0317                                              | 0.7539 | 0.7539                                             | 0.1780  | 0.1780                                            | 0.4783 | 0.0  | 0.5  | 0.3415    | nan |
| 0.1639        | 23.0  | 345  | 0.7914          | 1.0062 | 1.0062                                              | 0.7460 | 0.7460                                             | 0.2182  | 0.2182                                            | 0.4783 | 0.0  | 0.5  | 0.3415    | nan |
| 0.177         | 24.0  | 360  | 0.8619          | 1.0500 | 1.0500                                              | 0.7725 | 0.7725                                             | 0.1486  | 0.1486                                            | 0.4783 | 0.0  | 0.5  | 0.3415    | nan |
| 0.1473        | 25.0  | 375  | 0.8101          | 1.0180 | 1.0180                                              | 0.7587 | 0.7587                                             | 0.1997  | 0.1997                                            | 0.4783 | 0.0  | 0.5  | 0.3415    | nan |
| 0.181         | 26.0  | 390  | 0.8038          | 1.0141 | 1.0141                                              | 0.7433 | 0.7433                                             | 0.2059  | 0.2059                                            | 0.4783 | 0.0  | 0.5  | 0.3415    | nan |
| 0.1679        | 27.0  | 405  | 0.7982          | 1.0105 | 1.0105                                              | 0.7248 | 0.7248                                             | 0.2115  | 0.2115                                            | 0.4783 | 0.0  | 0.5  | 0.3415    | nan |
| 0.1529        | 28.0  | 420  | 0.8282          | 1.0293 | 1.0293                                              | 0.7454 | 0.7454                                             | 0.1818  | 0.1818                                            | 0.4783 | 0.0  | 0.5  | 0.3415    | nan |
| 0.1822        | 29.0  | 435  | 0.8310          | 1.0311 | 1.0311                                              | 0.7512 | 0.7512                                             | 0.1790  | 0.1790                                            | 0.4783 | 0.0  | 0.5  | 0.3415    | nan |
| 0.1442        | 30.0  | 450  | 0.8296          | 1.0302 | 1.0302                                              | 0.7515 | 0.7515                                             | 0.1804  | 0.1804                                            | 0.4783 | 0.0  | 0.5  | 0.3415    | nan |


### Framework versions

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