readme: ---
  license: mit
  tags:
  - generated_from_trainer
  model-index:
  - name: predict-perception-bertino-focus-assassin
    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-bertino-focus-assassin
  
  This model is a fine-tuned version of [indigo-ai/BERTino](https://huggingface.co/indigo-ai/BERTino) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3409
  - R2: 0.3205
  
  ## 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: 0.0001
  - 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: 47
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | R2     |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.5573        | 1.0   | 14   | 0.4856          | 0.0321 |
  | 0.1739        | 2.0   | 28   | 0.4735          | 0.0562 |
  | 0.0813        | 3.0   | 42   | 0.3416          | 0.3191 |
  | 0.0764        | 4.0   | 56   | 0.3613          | 0.2799 |
  | 0.0516        | 5.0   | 70   | 0.3264          | 0.3495 |
  | 0.0459        | 6.0   | 84   | 0.4193          | 0.1643 |
  | 0.0414        | 7.0   | 98   | 0.3502          | 0.3019 |
  | 0.028         | 8.0   | 112  | 0.3361          | 0.3301 |
  | 0.0281        | 9.0   | 126  | 0.3610          | 0.2804 |
  | 0.027         | 10.0  | 140  | 0.3523          | 0.2978 |
  | 0.0216        | 11.0  | 154  | 0.3440          | 0.3143 |
  | 0.0181        | 12.0  | 168  | 0.3506          | 0.3012 |
  | 0.013         | 13.0  | 182  | 0.3299          | 0.3424 |
  | 0.0116        | 14.0  | 196  | 0.3611          | 0.2803 |
  | 0.0118        | 15.0  | 210  | 0.3505          | 0.3013 |
  | 0.0139        | 16.0  | 224  | 0.3529          | 0.2967 |
  | 0.0099        | 17.0  | 238  | 0.3536          | 0.2952 |
  | 0.0096        | 18.0  | 252  | 0.3542          | 0.2941 |
  | 0.0107        | 19.0  | 266  | 0.3770          | 0.2486 |
  | 0.0088        | 20.0  | 280  | 0.3467          | 0.3091 |
  | 0.0065        | 21.0  | 294  | 0.3327          | 0.3369 |
  | 0.0073        | 22.0  | 308  | 0.3479          | 0.3066 |
  | 0.0062        | 23.0  | 322  | 0.3566          | 0.2893 |
  | 0.0063        | 24.0  | 336  | 0.3503          | 0.3019 |
  | 0.0057        | 25.0  | 350  | 0.3371          | 0.3282 |
  | 0.0049        | 26.0  | 364  | 0.3334          | 0.3355 |
  | 0.0045        | 27.0  | 378  | 0.3399          | 0.3225 |
  | 0.0049        | 28.0  | 392  | 0.3379          | 0.3266 |
  | 0.0049        | 29.0  | 406  | 0.3377          | 0.3268 |
  | 0.0055        | 30.0  | 420  | 0.3357          | 0.3309 |
  | 0.005         | 31.0  | 434  | 0.3394          | 0.3235 |
  | 0.0046        | 32.0  | 448  | 0.3432          | 0.3159 |
  | 0.0048        | 33.0  | 462  | 0.3427          | 0.3169 |
  | 0.0041        | 34.0  | 476  | 0.3450          | 0.3123 |
  | 0.0041        | 35.0  | 490  | 0.3436          | 0.3151 |
  | 0.0051        | 36.0  | 504  | 0.3394          | 0.3234 |
  | 0.0037        | 37.0  | 518  | 0.3370          | 0.3283 |
  | 0.004         | 38.0  | 532  | 0.3370          | 0.3284 |
  | 0.0033        | 39.0  | 546  | 0.3339          | 0.3344 |
  | 0.0034        | 40.0  | 560  | 0.3335          | 0.3352 |
  | 0.003         | 41.0  | 574  | 0.3373          | 0.3276 |
  | 0.0035        | 42.0  | 588  | 0.3380          | 0.3264 |
  | 0.0032        | 43.0  | 602  | 0.3382          | 0.3259 |
  | 0.0034        | 44.0  | 616  | 0.3432          | 0.3158 |
  | 0.003         | 45.0  | 630  | 0.3421          | 0.3181 |
  | 0.0027        | 46.0  | 644  | 0.3410          | 0.3203 |
  | 0.0037        | 47.0  | 658  | 0.3409          | 0.3205 |
  
  
  ### Framework versions
  
  - Transformers 4.16.2
  - Pytorch 1.10.2+cu113
  - Datasets 1.18.3
  - Tokenizers 0.11.0
  