--- license: mit tags: - generated_from_trainer model-index: - name: predict-perception-bert-focus-concept results: [] --- # 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