Gosse Minnema commited on
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update model card README.md
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README.md
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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-bertino-focus-victim
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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-bertino-focus-victim
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This model is a fine-tuned version of [indigo-ai/BERTino](https://huggingface.co/indigo-ai/BERTino) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2497
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- R2: 0.6131
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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: 0.0001
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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: 47
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | R2 |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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| 0.5438 | 1.0 | 14 | 0.4405 | 0.3175 |
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| 0.2336 | 2.0 | 28 | 0.2070 | 0.6792 |
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| 0.0986 | 3.0 | 42 | 0.2868 | 0.5555 |
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| 0.0907 | 4.0 | 56 | 0.2916 | 0.5481 |
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| 0.0652 | 5.0 | 70 | 0.2187 | 0.6611 |
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| 0.0591 | 6.0 | 84 | 0.2320 | 0.6406 |
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| 0.0478 | 7.0 | 98 | 0.2501 | 0.6125 |
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| 0.0347 | 8.0 | 112 | 0.2425 | 0.6243 |
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| 0.021 | 9.0 | 126 | 0.2670 | 0.5863 |
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| 0.0214 | 10.0 | 140 | 0.2853 | 0.5580 |
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| 0.0172 | 11.0 | 154 | 0.2726 | 0.5776 |
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| 0.0177 | 12.0 | 168 | 0.2629 | 0.5927 |
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| 0.0152 | 13.0 | 182 | 0.2396 | 0.6287 |
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| 0.012 | 14.0 | 196 | 0.2574 | 0.6012 |
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| 0.0119 | 15.0 | 210 | 0.2396 | 0.6288 |
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| 0.0128 | 16.0 | 224 | 0.2517 | 0.6100 |
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| 0.0109 | 17.0 | 238 | 0.2509 | 0.6112 |
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| 0.008 | 18.0 | 252 | 0.2522 | 0.6092 |
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| 0.0101 | 19.0 | 266 | 0.2503 | 0.6121 |
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| 0.0075 | 20.0 | 280 | 0.2527 | 0.6084 |
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| 0.0082 | 21.0 | 294 | 0.2544 | 0.6058 |
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| 0.0061 | 22.0 | 308 | 0.2510 | 0.6111 |
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| 0.006 | 23.0 | 322 | 0.2402 | 0.6279 |
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| 0.005 | 24.0 | 336 | 0.2539 | 0.6066 |
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| 0.0058 | 25.0 | 350 | 0.2438 | 0.6222 |
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| 0.0051 | 26.0 | 364 | 0.2439 | 0.6221 |
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| 0.006 | 27.0 | 378 | 0.2442 | 0.6216 |
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| 0.0061 | 28.0 | 392 | 0.2416 | 0.6257 |
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| 0.0053 | 29.0 | 406 | 0.2519 | 0.6097 |
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| 0.0045 | 30.0 | 420 | 0.2526 | 0.6085 |
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| 0.0034 | 31.0 | 434 | 0.2578 | 0.6006 |
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| 0.0039 | 32.0 | 448 | 0.2557 | 0.6038 |
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| 0.0043 | 33.0 | 462 | 0.2538 | 0.6068 |
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| 0.0041 | 34.0 | 476 | 0.2535 | 0.6072 |
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| 0.0042 | 35.0 | 490 | 0.2560 | 0.6033 |
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| 0.0037 | 36.0 | 504 | 0.2576 | 0.6009 |
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| 0.0036 | 37.0 | 518 | 0.2634 | 0.5919 |
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| 0.0037 | 38.0 | 532 | 0.2582 | 0.5999 |
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| 0.0038 | 39.0 | 546 | 0.2552 | 0.6045 |
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| 0.0034 | 40.0 | 560 | 0.2563 | 0.6028 |
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| 0.0033 | 41.0 | 574 | 0.2510 | 0.6110 |
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| 0.0029 | 42.0 | 588 | 0.2515 | 0.6103 |
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| 0.0033 | 43.0 | 602 | 0.2525 | 0.6088 |
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| 0.0028 | 44.0 | 616 | 0.2522 | 0.6093 |
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| 0.0028 | 45.0 | 630 | 0.2526 | 0.6085 |
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| 0.0027 | 46.0 | 644 | 0.2494 | 0.6136 |
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| 0.0024 | 47.0 | 658 | 0.2497 | 0.6131 |
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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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