| | --- |
| | license: mit |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: predict-perception-bertino-focus-object |
| | 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-object |
| |
|
| | 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: 0.2766 |
| | - R2: 0.5460 |
| |
|
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | | 0.4798 | 1.0 | 14 | 0.4519 | 0.2581 | |
| | | 0.2481 | 2.0 | 28 | 0.3042 | 0.5007 | |
| | | 0.12 | 3.0 | 42 | 0.3746 | 0.3851 | |
| | | 0.0969 | 4.0 | 56 | 0.3186 | 0.4770 | |
| | | 0.0907 | 5.0 | 70 | 0.3727 | 0.3882 | |
| | | 0.0673 | 6.0 | 84 | 0.2847 | 0.5327 | |
| | | 0.0457 | 7.0 | 98 | 0.3141 | 0.4844 | |
| | | 0.0431 | 8.0 | 112 | 0.3369 | 0.4470 | |
| | | 0.028 | 9.0 | 126 | 0.3039 | 0.5012 | |
| | | 0.0244 | 10.0 | 140 | 0.2964 | 0.5135 | |
| | | 0.0201 | 11.0 | 154 | 0.3072 | 0.4958 | |
| | | 0.0153 | 12.0 | 168 | 0.3049 | 0.4995 | |
| | | 0.0155 | 13.0 | 182 | 0.2924 | 0.5201 | |
| | | 0.015 | 14.0 | 196 | 0.2585 | 0.5757 | |
| | | 0.0181 | 15.0 | 210 | 0.3258 | 0.4652 | |
| | | 0.0136 | 16.0 | 224 | 0.3142 | 0.4842 | |
| | | 0.0105 | 17.0 | 238 | 0.2536 | 0.5837 | |
| | | 0.0104 | 18.0 | 252 | 0.2407 | 0.6050 | |
| | | 0.0107 | 19.0 | 266 | 0.2727 | 0.5524 | |
| | | 0.0084 | 20.0 | 280 | 0.3117 | 0.4883 | |
| | | 0.0102 | 21.0 | 294 | 0.2999 | 0.5078 | |
| | | 0.0074 | 22.0 | 308 | 0.3018 | 0.5047 | |
| | | 0.0068 | 23.0 | 322 | 0.2826 | 0.5361 | |
| | | 0.0054 | 24.0 | 336 | 0.2804 | 0.5398 | |
| | | 0.0044 | 25.0 | 350 | 0.2912 | 0.5220 | |
| | | 0.0048 | 26.0 | 364 | 0.2813 | 0.5382 | |
| | | 0.005 | 27.0 | 378 | 0.2933 | 0.5186 | |
| | | 0.0046 | 28.0 | 392 | 0.2820 | 0.5371 | |
| | | 0.004 | 29.0 | 406 | 0.2717 | 0.5541 | |
| | | 0.0054 | 30.0 | 420 | 0.2717 | 0.5540 | |
| | | 0.0042 | 31.0 | 434 | 0.2699 | 0.5570 | |
| | | 0.0033 | 32.0 | 448 | 0.2630 | 0.5684 | |
| | | 0.0038 | 33.0 | 462 | 0.2578 | 0.5767 | |
| | | 0.0032 | 34.0 | 476 | 0.2687 | 0.5589 | |
| | | 0.004 | 35.0 | 490 | 0.2737 | 0.5507 | |
| | | 0.0031 | 36.0 | 504 | 0.2753 | 0.5481 | |
| | | 0.0037 | 37.0 | 518 | 0.2819 | 0.5373 | |
| | | 0.0034 | 38.0 | 532 | 0.2759 | 0.5471 | |
| | | 0.0034 | 39.0 | 546 | 0.2835 | 0.5347 | |
| | | 0.0029 | 40.0 | 560 | 0.2814 | 0.5381 | |
| | | 0.0033 | 41.0 | 574 | 0.2801 | 0.5403 | |
| | | 0.0025 | 42.0 | 588 | 0.2759 | 0.5472 | |
| | | 0.0029 | 43.0 | 602 | 0.2790 | 0.5421 | |
| | | 0.0028 | 44.0 | 616 | 0.2801 | 0.5401 | |
| | | 0.003 | 45.0 | 630 | 0.2772 | 0.5451 | |
| | | 0.0028 | 46.0 | 644 | 0.2764 | 0.5463 | |
| | | 0.0026 | 47.0 | 658 | 0.2766 | 0.5460 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.16.2 |
| | - Pytorch 1.10.2+cu113 |
| | - Datasets 1.18.3 |
| | - Tokenizers 0.11.0 |
| |
|
