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predict-perception-bertino-focus-assassin
This model is a fine-tuned version of 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
