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--- |
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license: mit |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: predict-perception-bert-cause-human |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# predict-perception-bert-cause-human |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7139 |
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- Rmse: 1.2259 |
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- Rmse Cause::a Causata da un essere umano: 1.2259 |
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- Mae: 1.0480 |
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- Mae Cause::a Causata da un essere umano: 1.0480 |
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- R2: 0.4563 |
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- R2 Cause::a Causata da un essere umano: 0.4563 |
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- Cos: 0.4783 |
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- Pair: 0.0 |
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- Rank: 0.5 |
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- Neighbors: 0.3953 |
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- Rsa: nan |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 20 |
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- eval_batch_size: 8 |
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- seed: 1996 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rmse | Rmse Cause::a Causata da un essere umano | Mae | Mae Cause::a Causata da un essere umano | R2 | R2 Cause::a Causata da un essere umano | Cos | Pair | Rank | Neighbors | Rsa | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:----------------------------------------:|:------:|:---------------------------------------:|:------:|:--------------------------------------:|:------:|:----:|:----:|:---------:|:---:| |
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| 1.0874 | 1.0 | 15 | 1.2615 | 1.6296 | 1.6296 | 1.3836 | 1.3836 | 0.0393 | 0.0393 | 0.0435 | 0.0 | 0.5 | 0.2935 | nan | |
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| 0.9577 | 2.0 | 30 | 1.1988 | 1.5886 | 1.5886 | 1.3017 | 1.3017 | 0.0870 | 0.0870 | 0.4783 | 0.0 | 0.5 | 0.3944 | nan | |
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| 0.8414 | 3.0 | 45 | 0.9870 | 1.4414 | 1.4414 | 1.1963 | 1.1963 | 0.2483 | 0.2483 | 0.3913 | 0.0 | 0.5 | 0.3048 | nan | |
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| 0.7291 | 4.0 | 60 | 0.9098 | 1.3839 | 1.3839 | 1.1297 | 1.1297 | 0.3071 | 0.3071 | 0.4783 | 0.0 | 0.5 | 0.3084 | nan | |
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| 0.5949 | 5.0 | 75 | 0.9207 | 1.3921 | 1.3921 | 1.2079 | 1.2079 | 0.2988 | 0.2988 | 0.4783 | 0.0 | 0.5 | 0.3084 | nan | |
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| 0.4938 | 6.0 | 90 | 0.8591 | 1.3448 | 1.3448 | 1.1842 | 1.1842 | 0.3458 | 0.3458 | 0.4783 | 0.0 | 0.5 | 0.3084 | nan | |
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| 0.3611 | 7.0 | 105 | 0.8176 | 1.3119 | 1.3119 | 1.1454 | 1.1454 | 0.3774 | 0.3774 | 0.5652 | 0.0 | 0.5 | 0.4091 | nan | |
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| 0.2663 | 8.0 | 120 | 0.6879 | 1.2034 | 1.2034 | 1.0300 | 1.0300 | 0.4761 | 0.4761 | 0.5652 | 0.0 | 0.5 | 0.4091 | nan | |
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| 0.1833 | 9.0 | 135 | 0.7704 | 1.2735 | 1.2735 | 1.1031 | 1.1031 | 0.4133 | 0.4133 | 0.5652 | 0.0 | 0.5 | 0.3152 | nan | |
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| 0.1704 | 10.0 | 150 | 0.7097 | 1.2222 | 1.2222 | 1.0382 | 1.0382 | 0.4596 | 0.4596 | 0.4783 | 0.0 | 0.5 | 0.3084 | nan | |
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| 0.1219 | 11.0 | 165 | 0.6872 | 1.2027 | 1.2027 | 1.0198 | 1.0198 | 0.4767 | 0.4767 | 0.4783 | 0.0 | 0.5 | 0.3084 | nan | |
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| 0.1011 | 12.0 | 180 | 0.7201 | 1.2312 | 1.2312 | 1.0466 | 1.0466 | 0.4516 | 0.4516 | 0.5652 | 0.0 | 0.5 | 0.3152 | nan | |
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| 0.0849 | 13.0 | 195 | 0.7267 | 1.2368 | 1.2368 | 1.0454 | 1.0454 | 0.4466 | 0.4466 | 0.4783 | 0.0 | 0.5 | 0.3953 | nan | |
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| 0.0818 | 14.0 | 210 | 0.7361 | 1.2448 | 1.2448 | 1.0565 | 1.0565 | 0.4394 | 0.4394 | 0.4783 | 0.0 | 0.5 | 0.3953 | nan | |
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| 0.0634 | 15.0 | 225 | 0.7158 | 1.2275 | 1.2275 | 1.0384 | 1.0384 | 0.4549 | 0.4549 | 0.3913 | 0.0 | 0.5 | 0.3306 | nan | |
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| 0.065 | 16.0 | 240 | 0.7394 | 1.2475 | 1.2475 | 1.0659 | 1.0659 | 0.4369 | 0.4369 | 0.3913 | 0.0 | 0.5 | 0.3306 | nan | |
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| 0.0541 | 17.0 | 255 | 0.7642 | 1.2683 | 1.2683 | 1.0496 | 1.0496 | 0.4181 | 0.4181 | 0.4783 | 0.0 | 0.5 | 0.3953 | nan | |
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| 0.0577 | 18.0 | 270 | 0.7137 | 1.2257 | 1.2257 | 1.0303 | 1.0303 | 0.4565 | 0.4565 | 0.4783 | 0.0 | 0.5 | 0.3953 | nan | |
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| 0.0474 | 19.0 | 285 | 0.7393 | 1.2475 | 1.2475 | 1.0447 | 1.0447 | 0.4370 | 0.4370 | 0.4783 | 0.0 | 0.5 | 0.3084 | nan | |
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| 0.0494 | 20.0 | 300 | 0.7157 | 1.2274 | 1.2274 | 1.0453 | 1.0453 | 0.4550 | 0.4550 | 0.4783 | 0.0 | 0.5 | 0.3084 | nan | |
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| 0.0434 | 21.0 | 315 | 0.7248 | 1.2352 | 1.2352 | 1.0462 | 1.0462 | 0.4480 | 0.4480 | 0.4783 | 0.0 | 0.5 | 0.3953 | nan | |
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| 0.049 | 22.0 | 330 | 0.7384 | 1.2467 | 1.2467 | 1.0613 | 1.0613 | 0.4377 | 0.4377 | 0.4783 | 0.0 | 0.5 | 0.3953 | nan | |
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| 0.0405 | 23.0 | 345 | 0.7420 | 1.2498 | 1.2498 | 1.0653 | 1.0653 | 0.4349 | 0.4349 | 0.3913 | 0.0 | 0.5 | 0.3306 | nan | |
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| 0.0398 | 24.0 | 360 | 0.7355 | 1.2442 | 1.2442 | 1.0620 | 1.0620 | 0.4399 | 0.4399 | 0.4783 | 0.0 | 0.5 | 0.3953 | nan | |
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| 0.0398 | 25.0 | 375 | 0.7570 | 1.2623 | 1.2623 | 1.0698 | 1.0698 | 0.4235 | 0.4235 | 0.3913 | 0.0 | 0.5 | 0.3306 | nan | |
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| 0.0345 | 26.0 | 390 | 0.7359 | 1.2446 | 1.2446 | 1.0610 | 1.0610 | 0.4396 | 0.4396 | 0.5652 | 0.0 | 0.5 | 0.3152 | nan | |
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| 0.0345 | 27.0 | 405 | 0.7417 | 1.2495 | 1.2495 | 1.0660 | 1.0660 | 0.4352 | 0.4352 | 0.4783 | 0.0 | 0.5 | 0.3953 | nan | |
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| 0.0386 | 28.0 | 420 | 0.7215 | 1.2323 | 1.2323 | 1.0514 | 1.0514 | 0.4506 | 0.4506 | 0.4783 | 0.0 | 0.5 | 0.3084 | nan | |
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| 0.0372 | 29.0 | 435 | 0.7140 | 1.2260 | 1.2260 | 1.0477 | 1.0477 | 0.4562 | 0.4562 | 0.5652 | 0.0 | 0.5 | 0.4091 | nan | |
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| 0.0407 | 30.0 | 450 | 0.7139 | 1.2259 | 1.2259 | 1.0480 | 1.0480 | 0.4563 | 0.4563 | 0.4783 | 0.0 | 0.5 | 0.3953 | nan | |
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### Framework versions |
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- Transformers 4.16.2 |
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- Pytorch 1.10.2+cu113 |
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- Datasets 1.18.3 |
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- Tokenizers 0.11.0 |
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