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---
license: cc-by-4.0
tags:
- generated_from_trainer
datasets:
- null
model-index:
- name: nbailab-base-ner-scandi-unbalanced
results:
- task:
name: Token Classification
type: token-classification
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# nbailab-base-ner-scandi-unbalanced
This model is a fine-tuned version of [NbAiLab/nb-bert-base](https://huggingface.co/NbAiLab/nb-bert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0666
- Micro F1: 0.8693
- Micro F1 No Misc: 0.8925
## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 90135.90000000001
- num_epochs: 1000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Micro F1 | Micro F1 No Misc |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:----------------:|
| 0.6682 | 1.0 | 2816 | 0.0872 | 0.6916 | 0.7306 |
| 0.0684 | 2.0 | 5632 | 0.0464 | 0.8167 | 0.8538 |
| 0.0444 | 3.0 | 8448 | 0.0367 | 0.8485 | 0.8783 |
| 0.0349 | 4.0 | 11264 | 0.0316 | 0.8684 | 0.8920 |
| 0.0282 | 5.0 | 14080 | 0.0290 | 0.8820 | 0.9033 |
| 0.0231 | 6.0 | 16896 | 0.0283 | 0.8854 | 0.9060 |
| 0.0189 | 7.0 | 19712 | 0.0253 | 0.8964 | 0.9156 |
| 0.0155 | 8.0 | 22528 | 0.0260 | 0.9016 | 0.9201 |
| 0.0123 | 9.0 | 25344 | 0.0266 | 0.9059 | 0.9233 |
| 0.0098 | 10.0 | 28160 | 0.0280 | 0.9091 | 0.9279 |
| 0.008 | 11.0 | 30976 | 0.0309 | 0.9093 | 0.9287 |
| 0.0065 | 12.0 | 33792 | 0.0313 | 0.9103 | 0.9284 |
| 0.0053 | 13.0 | 36608 | 0.0322 | 0.9078 | 0.9257 |
| 0.0046 | 14.0 | 39424 | 0.0343 | 0.9075 | 0.9256 |
### Framework versions
- Transformers 4.10.3
- Pytorch 1.9.0+cu102
- Datasets 1.12.1
- Tokenizers 0.10.3
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