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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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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: pos_final_mono_nl |
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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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# pos_final_mono_nl |
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This model is a fine-tuned version of [pdelobelle/robbert-v2-dutch-base](https://huggingface.co/pdelobelle/robbert-v2-dutch-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1115 |
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- Precision: 0.9783 |
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- Recall: 0.9784 |
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- F1: 0.9783 |
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- Accuracy: 0.9791 |
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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: 5e-05 |
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- train_batch_size: 256 |
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- eval_batch_size: 256 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 1024 |
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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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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 40.0 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 69 | 3.7703 | 0.2597 | 0.1252 | 0.1689 | 0.2575 | |
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| No log | 2.0 | 138 | 1.0148 | 0.8058 | 0.8008 | 0.8033 | 0.8066 | |
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| No log | 3.0 | 207 | 0.3402 | 0.9302 | 0.9278 | 0.9290 | 0.9299 | |
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| No log | 4.0 | 276 | 0.2016 | 0.9559 | 0.9551 | 0.9555 | 0.9561 | |
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| No log | 5.0 | 345 | 0.1486 | 0.9643 | 0.9638 | 0.9641 | 0.9648 | |
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| No log | 6.0 | 414 | 0.1206 | 0.9697 | 0.9696 | 0.9697 | 0.9702 | |
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| No log | 7.0 | 483 | 0.1063 | 0.9720 | 0.9719 | 0.9720 | 0.9727 | |
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| 1.2192 | 8.0 | 552 | 0.0983 | 0.9734 | 0.9735 | 0.9735 | 0.9742 | |
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| 1.2192 | 9.0 | 621 | 0.0947 | 0.9746 | 0.9747 | 0.9746 | 0.9754 | |
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| 1.2192 | 10.0 | 690 | 0.0913 | 0.9753 | 0.9755 | 0.9754 | 0.9761 | |
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| 1.2192 | 11.0 | 759 | 0.0885 | 0.9761 | 0.9763 | 0.9762 | 0.9770 | |
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| 1.2192 | 12.0 | 828 | 0.0877 | 0.9764 | 0.9765 | 0.9764 | 0.9772 | |
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| 1.2192 | 13.0 | 897 | 0.0878 | 0.9767 | 0.9769 | 0.9768 | 0.9775 | |
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| 1.2192 | 14.0 | 966 | 0.0873 | 0.9767 | 0.9769 | 0.9768 | 0.9776 | |
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| 0.0688 | 15.0 | 1035 | 0.0877 | 0.9771 | 0.9773 | 0.9772 | 0.9779 | |
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| 0.0688 | 16.0 | 1104 | 0.0878 | 0.9773 | 0.9774 | 0.9773 | 0.9781 | |
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| 0.0688 | 17.0 | 1173 | 0.0897 | 0.9772 | 0.9773 | 0.9773 | 0.9781 | |
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| 0.0688 | 18.0 | 1242 | 0.0909 | 0.9775 | 0.9776 | 0.9776 | 0.9783 | |
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| 0.0688 | 19.0 | 1311 | 0.0917 | 0.9776 | 0.9778 | 0.9777 | 0.9785 | |
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| 0.0688 | 20.0 | 1380 | 0.0924 | 0.9778 | 0.9780 | 0.9779 | 0.9787 | |
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| 0.0688 | 21.0 | 1449 | 0.0949 | 0.9777 | 0.9779 | 0.9778 | 0.9785 | |
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| 0.0366 | 22.0 | 1518 | 0.0956 | 0.9776 | 0.9777 | 0.9777 | 0.9784 | |
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| 0.0366 | 23.0 | 1587 | 0.0962 | 0.9778 | 0.9780 | 0.9779 | 0.9786 | |
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| 0.0366 | 24.0 | 1656 | 0.0992 | 0.9777 | 0.9780 | 0.9779 | 0.9786 | |
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| 0.0366 | 25.0 | 1725 | 0.0999 | 0.9779 | 0.9781 | 0.9780 | 0.9787 | |
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| 0.0366 | 26.0 | 1794 | 0.1007 | 0.9780 | 0.9782 | 0.9781 | 0.9789 | |
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| 0.0366 | 27.0 | 1863 | 0.1022 | 0.9781 | 0.9782 | 0.9782 | 0.9789 | |
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| 0.0366 | 28.0 | 1932 | 0.1030 | 0.9781 | 0.9783 | 0.9782 | 0.9790 | |
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| 0.0226 | 29.0 | 2001 | 0.1055 | 0.9781 | 0.9782 | 0.9781 | 0.9789 | |
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| 0.0226 | 30.0 | 2070 | 0.1057 | 0.9780 | 0.9782 | 0.9781 | 0.9789 | |
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| 0.0226 | 31.0 | 2139 | 0.1067 | 0.9780 | 0.9781 | 0.9780 | 0.9788 | |
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| 0.0226 | 32.0 | 2208 | 0.1077 | 0.9780 | 0.9782 | 0.9781 | 0.9789 | |
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| 0.0226 | 33.0 | 2277 | 0.1085 | 0.9780 | 0.9781 | 0.9781 | 0.9789 | |
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| 0.0226 | 34.0 | 2346 | 0.1094 | 0.9781 | 0.9782 | 0.9781 | 0.9789 | |
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| 0.0226 | 35.0 | 2415 | 0.1095 | 0.9783 | 0.9784 | 0.9783 | 0.9791 | |
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| 0.0226 | 36.0 | 2484 | 0.1101 | 0.9780 | 0.9782 | 0.9781 | 0.9789 | |
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| 0.0159 | 37.0 | 2553 | 0.1114 | 0.9782 | 0.9784 | 0.9783 | 0.9791 | |
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| 0.0159 | 38.0 | 2622 | 0.1111 | 0.9782 | 0.9784 | 0.9783 | 0.9791 | |
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| 0.0159 | 39.0 | 2691 | 0.1114 | 0.9782 | 0.9784 | 0.9783 | 0.9791 | |
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| 0.0159 | 40.0 | 2760 | 0.1115 | 0.9783 | 0.9784 | 0.9783 | 0.9791 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.12.0 |
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- Datasets 2.18.0 |
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- Tokenizers 0.13.2 |
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