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detect-femicide-news-xlmr-nl-mono-freeze2

Text Classification
Transformers
PyTorch
TensorBoard
xlm-roberta
Generated from Trainer
Inference Endpoints
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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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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: detect-femicide-news-xlmr-nl-mono-freeze2
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+ results: []
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+ ---
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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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+
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+ # detect-femicide-news-xlmr-nl-mono-freeze2
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+
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+ This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6487
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+ - Accuracy: 0.6429
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+ - Precision Neg: 0.6429
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+ - Precision Pos: 0.0
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+ - Recall Neg: 1.0
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+ - Recall Pos: 0.0
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+ - F1 Score Neg: 0.7826
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+ - F1 Score Pos: 0.0
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 24
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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: 100
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision Neg | Precision Pos | Recall Neg | Recall Pos | F1 Score Neg | F1 Score Pos |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:-------------:|:----------:|:----------:|:------------:|:------------:|
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+ | 0.7312 | 1.0 | 23 | 0.7413 | 0.3571 | 0.0 | 0.3571 | 0.0 | 1.0 | 0.0 | 0.5263 |
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+ | 0.7151 | 2.0 | 46 | 0.7177 | 0.3571 | 0.0 | 0.3571 | 0.0 | 1.0 | 0.0 | 0.5263 |
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+ | 0.7049 | 3.0 | 69 | 0.6988 | 0.3571 | 0.0 | 0.3571 | 0.0 | 1.0 | 0.0 | 0.5263 |
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+ | 0.6934 | 4.0 | 92 | 0.6945 | 0.3571 | 0.0 | 0.3571 | 0.0 | 1.0 | 0.0 | 0.5263 |
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+ | 0.6886 | 5.0 | 115 | 0.6903 | 0.6071 | 0.8182 | 0.4706 | 0.5 | 0.8 | 0.6207 | 0.5926 |
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+ | 0.6911 | 6.0 | 138 | 0.6846 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6856 | 7.0 | 161 | 0.6786 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6888 | 8.0 | 184 | 0.6783 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6862 | 9.0 | 207 | 0.6819 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6807 | 10.0 | 230 | 0.6758 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6839 | 11.0 | 253 | 0.6721 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6878 | 12.0 | 276 | 0.6708 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6799 | 13.0 | 299 | 0.6692 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6813 | 14.0 | 322 | 0.6673 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6792 | 15.0 | 345 | 0.6676 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6774 | 16.0 | 368 | 0.6683 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6807 | 17.0 | 391 | 0.6679 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6834 | 18.0 | 414 | 0.6693 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6784 | 19.0 | 437 | 0.6679 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.676 | 20.0 | 460 | 0.6698 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6791 | 21.0 | 483 | 0.6661 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6775 | 22.0 | 506 | 0.6633 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6688 | 23.0 | 529 | 0.6589 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6748 | 24.0 | 552 | 0.6580 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6771 | 25.0 | 575 | 0.6619 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6761 | 26.0 | 598 | 0.6639 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6773 | 27.0 | 621 | 0.6651 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6737 | 28.0 | 644 | 0.6656 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6721 | 29.0 | 667 | 0.6650 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6683 | 30.0 | 690 | 0.6612 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6663 | 31.0 | 713 | 0.6592 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6724 | 32.0 | 736 | 0.6576 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6739 | 33.0 | 759 | 0.6601 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6691 | 34.0 | 782 | 0.6602 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6652 | 35.0 | 805 | 0.6588 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6717 | 36.0 | 828 | 0.6596 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6637 | 37.0 | 851 | 0.6587 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6704 | 38.0 | 874 | 0.6579 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6608 | 39.0 | 897 | 0.6599 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6615 | 40.0 | 920 | 0.6580 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6662 | 41.0 | 943 | 0.6592 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6622 | 42.0 | 966 | 0.6616 | 0.6071 | 0.6296 | 0.0 | 0.9444 | 0.0 | 0.7556 | 0.0 |
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+ | 0.664 | 43.0 | 989 | 0.6610 | 0.6071 | 0.6296 | 0.0 | 0.9444 | 0.0 | 0.7556 | 0.0 |
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+ | 0.6695 | 44.0 | 1012 | 0.6570 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6677 | 45.0 | 1035 | 0.6557 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6705 | 46.0 | 1058 | 0.6546 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6591 | 47.0 | 1081 | 0.6547 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6675 | 48.0 | 1104 | 0.6532 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6622 | 49.0 | 1127 | 0.6544 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6571 | 50.0 | 1150 | 0.6552 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6678 | 51.0 | 1173 | 0.6555 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6596 | 52.0 | 1196 | 0.6544 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6583 | 53.0 | 1219 | 0.6517 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6641 | 54.0 | 1242 | 0.6508 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.671 | 55.0 | 1265 | 0.6502 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6645 | 56.0 | 1288 | 0.6513 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6604 | 57.0 | 1311 | 0.6510 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6644 | 58.0 | 1334 | 0.6509 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6617 | 59.0 | 1357 | 0.6528 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6608 | 60.0 | 1380 | 0.6536 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6533 | 61.0 | 1403 | 0.6533 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6596 | 62.0 | 1426 | 0.6518 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6607 | 63.0 | 1449 | 0.6511 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.658 | 64.0 | 1472 | 0.6509 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6546 | 65.0 | 1495 | 0.6514 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6613 | 66.0 | 1518 | 0.6516 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.662 | 67.0 | 1541 | 0.6506 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.661 | 68.0 | 1564 | 0.6503 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6571 | 69.0 | 1587 | 0.6497 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6656 | 70.0 | 1610 | 0.6500 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6637 | 71.0 | 1633 | 0.6508 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6519 | 72.0 | 1656 | 0.6518 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6593 | 73.0 | 1679 | 0.6516 | 0.6071 | 0.6296 | 0.0 | 0.9444 | 0.0 | 0.7556 | 0.0 |
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+ | 0.6539 | 74.0 | 1702 | 0.6514 | 0.6071 | 0.6296 | 0.0 | 0.9444 | 0.0 | 0.7556 | 0.0 |
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+ | 0.6568 | 75.0 | 1725 | 0.6506 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6581 | 76.0 | 1748 | 0.6504 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6557 | 77.0 | 1771 | 0.6499 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6542 | 78.0 | 1794 | 0.6500 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6557 | 79.0 | 1817 | 0.6498 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6637 | 80.0 | 1840 | 0.6493 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6603 | 81.0 | 1863 | 0.6490 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6568 | 82.0 | 1886 | 0.6485 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6561 | 83.0 | 1909 | 0.6490 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6665 | 84.0 | 1932 | 0.6499 | 0.6071 | 0.6296 | 0.0 | 0.9444 | 0.0 | 0.7556 | 0.0 |
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+ | 0.655 | 85.0 | 1955 | 0.6492 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6509 | 86.0 | 1978 | 0.6493 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6549 | 87.0 | 2001 | 0.6493 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.655 | 88.0 | 2024 | 0.6489 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6576 | 89.0 | 2047 | 0.6493 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6612 | 90.0 | 2070 | 0.6492 | 0.6071 | 0.6296 | 0.0 | 0.9444 | 0.0 | 0.7556 | 0.0 |
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+ | 0.6641 | 91.0 | 2093 | 0.6492 | 0.6071 | 0.6296 | 0.0 | 0.9444 | 0.0 | 0.7556 | 0.0 |
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+ | 0.654 | 92.0 | 2116 | 0.6487 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6556 | 93.0 | 2139 | 0.6488 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6566 | 94.0 | 2162 | 0.6486 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6565 | 95.0 | 2185 | 0.6487 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6516 | 96.0 | 2208 | 0.6488 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6509 | 97.0 | 2231 | 0.6487 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6588 | 98.0 | 2254 | 0.6487 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6532 | 99.0 | 2277 | 0.6487 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+ | 0.6548 | 100.0 | 2300 | 0.6487 | 0.6429 | 0.6429 | 0.0 | 1.0 | 0.0 | 0.7826 | 0.0 |
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+
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+
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+ ### Framework versions
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+
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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