--- base_model: MiMe-MeMo/MeMo-BERT-03 tags: - generated_from_trainer model-index: - name: MeMo-BERT-WSD results: [] language: da # <-- my language widget: - text: "Men havde Gud vendt sig fra ham , saa kunde han ogsaa vende sig fra Gud . Havde Gud ingen Øren , saa havde han heller ingen Læber , havde Gud ingen Naade , saa havde han heller ingen Tilbedelse , og han trodsede og viste Gud ud af sit Hjærte ." --- # MeMo-BERT-WSD This model is a fine-tuned version of [MiMe-MeMo/MeMo-BERT-03](https://huggingface.co/MiMe-MeMo/MeMo-BERT-03) on https://huggingface.co/MiMe-MeMo/MeMo-Dataset-WSD dataset. It achieves the following results on the evaluation set: - Loss: 3.1503 - F1-score: 0.5541 ## 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: 5e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 20 ### Training results | Training Loss | Epoch | Step | Validation Loss | F1-score | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 61 | 1.3445 | 0.2569 | | No log | 2.0 | 122 | 1.0424 | 0.5124 | | No log | 3.0 | 183 | 1.1609 | 0.5304 | | No log | 4.0 | 244 | 1.3851 | 0.5389 | | No log | 5.0 | 305 | 1.9822 | 0.4456 | | No log | 6.0 | 366 | 2.0347 | 0.4914 | | No log | 7.0 | 427 | 2.9891 | 0.4419 | | No log | 8.0 | 488 | 2.5316 | 0.5183 | | 0.4858 | 9.0 | 549 | 2.5900 | 0.5419 | | 0.4858 | 10.0 | 610 | 2.9300 | 0.5051 | | 0.4858 | 11.0 | 671 | 3.0018 | 0.5211 | | 0.4858 | 12.0 | 732 | 3.0486 | 0.5109 | | 0.4858 | 13.0 | 793 | 3.0887 | 0.5337 | | 0.4858 | 14.0 | 854 | 3.1180 | 0.5441 | | 0.4858 | 15.0 | 915 | 3.1503 | 0.5541 | | 0.4858 | 16.0 | 976 | 3.1649 | 0.5436 | | 0.0041 | 17.0 | 1037 | 3.1925 | 0.5436 | | 0.0041 | 18.0 | 1098 | 3.2019 | 0.5436 | | 0.0041 | 19.0 | 1159 | 3.2089 | 0.5436 | | 0.0041 | 20.0 | 1220 | 3.2116 | 0.5436 | ### Framework versions - Transformers 4.38.2 - Pytorch 2.2.1+cu121 - Datasets 2.18.0 - Tokenizers 0.15.2