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--- |
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license: cc-by-4.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- null |
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model-index: |
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- name: nbailab-base-ner-scandi-unbalanced |
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results: |
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- task: |
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name: Token Classification |
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type: token-classification |
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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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# nbailab-base-ner-scandi-unbalanced |
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This model is a fine-tuned version of [NbAiLab/nb-bert-base](https://huggingface.co/NbAiLab/nb-bert-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0666 |
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- Micro F1: 0.8693 |
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- Micro F1 No Misc: 0.8925 |
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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: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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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: 90135.90000000001 |
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- num_epochs: 1000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Micro F1 | Micro F1 No Misc | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:----------------:| |
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| 0.6682 | 1.0 | 2816 | 0.0872 | 0.6916 | 0.7306 | |
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| 0.0684 | 2.0 | 5632 | 0.0464 | 0.8167 | 0.8538 | |
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| 0.0444 | 3.0 | 8448 | 0.0367 | 0.8485 | 0.8783 | |
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| 0.0349 | 4.0 | 11264 | 0.0316 | 0.8684 | 0.8920 | |
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| 0.0282 | 5.0 | 14080 | 0.0290 | 0.8820 | 0.9033 | |
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| 0.0231 | 6.0 | 16896 | 0.0283 | 0.8854 | 0.9060 | |
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| 0.0189 | 7.0 | 19712 | 0.0253 | 0.8964 | 0.9156 | |
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| 0.0155 | 8.0 | 22528 | 0.0260 | 0.9016 | 0.9201 | |
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| 0.0123 | 9.0 | 25344 | 0.0266 | 0.9059 | 0.9233 | |
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| 0.0098 | 10.0 | 28160 | 0.0280 | 0.9091 | 0.9279 | |
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| 0.008 | 11.0 | 30976 | 0.0309 | 0.9093 | 0.9287 | |
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| 0.0065 | 12.0 | 33792 | 0.0313 | 0.9103 | 0.9284 | |
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| 0.0053 | 13.0 | 36608 | 0.0322 | 0.9078 | 0.9257 | |
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| 0.0046 | 14.0 | 39424 | 0.0343 | 0.9075 | 0.9256 | |
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### Framework versions |
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- Transformers 4.10.3 |
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- Pytorch 1.9.0+cu102 |
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- Datasets 1.12.1 |
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- Tokenizers 0.10.3 |
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