---
license: cc-by-4.0
tags:
- generated_from_trainer
model-index:
- name: contract-ner-model-da
  results: []
---

<!-- 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. -->

# contract-ner-model-da

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: 0.0213
- Micro F1: 0.9217

## 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: 201
- num_epochs: 500

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Micro F1 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.2722        | 4.44   | 200  | 0.0318          | 0.6422   |
| 0.0182        | 8.88   | 400  | 0.0176          | 0.8321   |
| 0.0081        | 13.33  | 600  | 0.0202          | 0.8530   |
| 0.0045        | 17.77  | 800  | 0.0168          | 0.8839   |
| 0.0029        | 22.22  | 1000 | 0.0230          | 0.8758   |
| 0.0016        | 26.66  | 1200 | 0.0234          | 0.8690   |
| 0.0013        | 31.11  | 1400 | 0.0219          | 0.8853   |
| 0.0012        | 35.55  | 1600 | 0.0248          | 0.8831   |
| 0.0008        | 39.99  | 1800 | 0.0223          | 0.8979   |
| 0.0006        | 44.44  | 2000 | 0.0257          | 0.8752   |
| 0.0004        | 48.88  | 2200 | 0.0191          | 0.9018   |
| 0.0004        | 53.33  | 2400 | 0.0244          | 0.9029   |
| 0.0004        | 57.77  | 2600 | 0.0227          | 0.8986   |
| 0.0007        | 62.22  | 2800 | 0.0242          | 0.9004   |
| 0.0004        | 66.66  | 3000 | 0.0218          | 0.8937   |
| 0.0003        | 71.11  | 3200 | 0.0214          | 0.9039   |
| 0.0003        | 75.55  | 3400 | 0.0251          | 0.8958   |
| 0.0003        | 79.99  | 3600 | 0.0210          | 0.8943   |
| 0.0004        | 84.44  | 3800 | 0.0227          | 0.8995   |
| 0.0002        | 88.88  | 4000 | 0.0226          | 0.9116   |
| 0.0002        | 93.33  | 4200 | 0.0209          | 0.9121   |
| 0.0001        | 97.77  | 4400 | 0.0225          | 0.9105   |
| 0.0003        | 102.22 | 4600 | 0.0278          | 0.9039   |
| 0.0003        | 106.66 | 4800 | 0.0223          | 0.9009   |
| 0.0002        | 111.11 | 5000 | 0.0274          | 0.9123   |
| 0.0003        | 115.55 | 5200 | 0.0236          | 0.9123   |
| 0.0001        | 119.99 | 5400 | 0.0235          | 0.9059   |
| 0.0001        | 124.44 | 5600 | 0.0220          | 0.9165   |
| 0.0002        | 128.88 | 5800 | 0.0265          | 0.9021   |
| 0.0001        | 133.33 | 6000 | 0.0225          | 0.9029   |
| 0.0002        | 137.77 | 6200 | 0.0249          | 0.9166   |
| 0.0004        | 142.22 | 6400 | 0.0192          | 0.9128   |
| 0.0002        | 146.66 | 6600 | 0.0181          | 0.9313   |
| 0.0001        | 151.11 | 6800 | 0.0191          | 0.9269   |
| 0.0001        | 155.55 | 7000 | 0.0224          | 0.9154   |
| 0.0002        | 159.99 | 7200 | 0.0192          | 0.9171   |
| 0.0002        | 164.44 | 7400 | 0.0202          | 0.9217   |
| 0.0001        | 168.88 | 7600 | 0.0185          | 0.9171   |
| 0.0001        | 173.33 | 7800 | 0.0207          | 0.9201   |
| 0.0001        | 177.77 | 8000 | 0.0226          | 0.9121   |
| 0.0001        | 182.22 | 8200 | 0.0208          | 0.9191   |
| 0.0002        | 186.66 | 8400 | 0.0248          | 0.9184   |
| 0.0002        | 191.11 | 8600 | 0.0213          | 0.9217   |


### Framework versions

- Transformers 4.11.3
- Pytorch 1.9.0+cu111
- Datasets 1.14.0
- Tokenizers 0.10.3