pytorch tensorboard bert text-classification transformers generated_from_trainer license:mit model-index
---
license: mit
tags:
- generated_from_trainer
model-index:
- name: predict-perception-bert-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-bert-focus-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: 0.8129
- Rmse: 1.0197
- Rmse Focus::a Su un concetto astratto o un'emozione: 1.0197
- Mae: 0.7494
- Mae Focus::a Su un concetto astratto o un'emozione: 0.7494
- R2: 0.1970
- R2 Focus::a Su un concetto astratto o un'emozione: 0.1970
- Cos: 0.4783
- Pair: 0.0
- Rank: 0.5
- Neighbors: 0.4667
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------------------------------------------------:|:------:|:--------------------------------------------------:|:-------:|:-------------------------------------------------:|:------:|:----:|:----:|:---------:|:---:|
| 1.047         | 1.0   | 15   | 1.0199          | 1.1422 | 1.1422                                              | 0.9321 | 0.9321                                             | -0.0075 | -0.0075                                           | 0.1304 | 0.0  | 0.5  | 0.3199    | nan |
| 0.9914        | 2.0   | 30   | 0.9724          | 1.1153 | 1.1153                                              | 0.9407 | 0.9407                                             | 0.0393  | 0.0393                                            | 0.2174 | 0.0  | 0.5  | 0.3954    | nan |
| 0.9049        | 3.0   | 45   | 0.9406          | 1.0969 | 1.0969                                              | 0.9170 | 0.9170                                             | 0.0708  | 0.0708                                            | 0.2174 | 0.0  | 0.5  | 0.3632    | nan |
| 0.8826        | 4.0   | 60   | 0.8553          | 1.0460 | 1.0460                                              | 0.8570 | 0.8570                                             | 0.1551  | 0.1551                                            | 0.2174 | 0.0  | 0.5  | 0.3230    | nan |
| 0.7837        | 5.0   | 75   | 0.8324          | 1.0319 | 1.0319                                              | 0.8683 | 0.8683                                             | 0.1776  | 0.1776                                            | 0.2174 | 0.0  | 0.5  | 0.3419    | nan |
| 0.7013        | 6.0   | 90   | 0.7737          | 0.9949 | 0.9949                                              | 0.8150 | 0.8150                                             | 0.2356  | 0.2356                                            | 0.5652 | 0.0  | 0.5  | 0.5023    | nan |
| 0.6429        | 7.0   | 105  | 0.7832          | 1.0010 | 1.0010                                              | 0.8005 | 0.8005                                             | 0.2262  | 0.2262                                            | 0.3913 | 0.0  | 0.5  | 0.4446    | nan |
| 0.5526        | 8.0   | 120  | 0.7734          | 0.9946 | 0.9946                                              | 0.7704 | 0.7704                                             | 0.2360  | 0.2360                                            | 0.3043 | 0.0  | 0.5  | 0.2923    | nan |
| 0.5194        | 9.0   | 135  | 0.6624          | 0.9205 | 0.9205                                              | 0.7013 | 0.7013                                             | 0.3456  | 0.3456                                            | 0.3913 | 0.0  | 0.5  | 0.3523    | nan |
| 0.4278        | 10.0  | 150  | 0.8255          | 1.0276 | 1.0276                                              | 0.7351 | 0.7351                                             | 0.1845  | 0.1845                                            | 0.3043 | 0.0  | 0.5  | 0.4349    | nan |
| 0.3522        | 11.0  | 165  | 0.9340          | 1.0931 | 1.0931                                              | 0.8069 | 0.8069                                             | 0.0773  | 0.0773                                            | 0.3913 | 0.0  | 0.5  | 0.4059    | nan |
| 0.314         | 12.0  | 180  | 0.7495          | 0.9792 | 0.9792                                              | 0.7254 | 0.7254                                             | 0.2596  | 0.2596                                            | 0.3913 | 0.0  | 0.5  | 0.4059    | nan |
| 0.2665        | 13.0  | 195  | 0.8574          | 1.0473 | 1.0473                                              | 0.7678 | 0.7678                                             | 0.1530  | 0.1530                                            | 0.3913 | 0.0  | 0.5  | 0.4059    | nan |
| 0.2348        | 14.0  | 210  | 0.7913          | 1.0061 | 1.0061                                              | 0.7218 | 0.7218                                             | 0.2183  | 0.2183                                            | 0.3913 | 0.0  | 0.5  | 0.4059    | nan |
| 0.1859        | 15.0  | 225  | 0.8012          | 1.0124 | 1.0124                                              | 0.7162 | 0.7162                                             | 0.2085  | 0.2085                                            | 0.3913 | 0.0  | 0.5  | 0.4059    | nan |
| 0.1373        | 16.0  | 240  | 0.8405          | 1.0369 | 1.0369                                              | 0.7318 | 0.7318                                             | 0.1697  | 0.1697                                            | 0.3043 | 0.0  | 0.5  | 0.3734    | nan |
| 0.1245        | 17.0  | 255  | 0.8398          | 1.0365 | 1.0365                                              | 0.7455 | 0.7455                                             | 0.1703  | 0.1703                                            | 0.4783 | 0.0  | 0.5  | 0.4667    | nan |
| 0.1148        | 18.0  | 270  | 0.7948          | 1.0083 | 1.0083                                              | 0.7140 | 0.7140                                             | 0.2148  | 0.2148                                            | 0.3913 | 0.0  | 0.5  | 0.4175    | nan |
| 0.1187        | 19.0  | 285  | 0.8301          | 1.0305 | 1.0305                                              | 0.7381 | 0.7381                                             | 0.1799  | 0.1799                                            | 0.3913 | 0.0  | 0.5  | 0.4175    | nan |
| 0.1236        | 20.0  | 300  | 0.8867          | 1.0650 | 1.0650                                              | 0.7879 | 0.7879                                             | 0.1240  | 0.1240                                            | 0.3913 | 0.0  | 0.5  | 0.4059    | nan |
| 0.1101        | 21.0  | 315  | 0.8405          | 1.0369 | 1.0369                                              | 0.7632 | 0.7632                                             | 0.1696  | 0.1696                                            | 0.3913 | 0.0  | 0.5  | 0.4059    | nan |
| 0.0902        | 22.0  | 330  | 0.7850          | 1.0021 | 1.0021                                              | 0.7173 | 0.7173                                             | 0.2245  | 0.2245                                            | 0.3043 | 0.0  | 0.5  | 0.3734    | nan |
| 0.093         | 23.0  | 345  | 0.7386          | 0.9720 | 0.9720                                              | 0.6960 | 0.6960                                             | 0.2704  | 0.2704                                            | 0.3913 | 0.0  | 0.5  | 0.4175    | nan |
| 0.0846        | 24.0  | 360  | 0.7748          | 0.9956 | 0.9956                                              | 0.7150 | 0.7150                                             | 0.2345  | 0.2345                                            | 0.3913 | 0.0  | 0.5  | 0.4175    | nan |
| 0.0826        | 25.0  | 375  | 0.7951          | 1.0085 | 1.0085                                              | 0.7230 | 0.7230                                             | 0.2145  | 0.2145                                            | 0.3913 | 0.0  | 0.5  | 0.4175    | nan |
| 0.0749        | 26.0  | 390  | 0.8470          | 1.0409 | 1.0409                                              | 0.7621 | 0.7621                                             | 0.1633  | 0.1633                                            | 0.4783 | 0.0  | 0.5  | 0.4667    | nan |
| 0.069         | 27.0  | 405  | 0.7968          | 1.0096 | 1.0096                                              | 0.7275 | 0.7275                                             | 0.2129  | 0.2129                                            | 0.3913 | 0.0  | 0.5  | 0.4175    | nan |
| 0.0775        | 28.0  | 420  | 0.8298          | 1.0303 | 1.0303                                              | 0.7589 | 0.7589                                             | 0.1802  | 0.1802                                            | 0.4783 | 0.0  | 0.5  | 0.4667    | nan |
| 0.0783        | 29.0  | 435  | 0.8113          | 1.0188 | 1.0188                                              | 0.7469 | 0.7469                                             | 0.1985  | 0.1985                                            | 0.4783 | 0.0  | 0.5  | 0.4667    | nan |
| 0.0773        | 30.0  | 450  | 0.8129          | 1.0197 | 1.0197                                              | 0.7494 | 0.7494                                             | 0.1970  | 0.1970                                            | 0.4783 | 0.0  | 0.5  | 0.4667    | nan |


### Framework versions

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