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---
base_model: KBLab/bert-base-swedish-cased-ner
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: testThesisSmallSMP
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. -->
# testThesisSmallSMP
This model is a fine-tuned version of [KBLab/bert-base-swedish-cased-ner](https://huggingface.co./KBLab/bert-base-swedish-cased-ner) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3275
- Precision: 0.6826
- Recall: 0.6477
- F1: 0.6647
- Accuracy: 0.8940
## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 39 | 0.4518 | 0.4107 | 0.2614 | 0.3194 | 0.8555 |
| No log | 2.0 | 78 | 0.3469 | 0.6687 | 0.6193 | 0.6431 | 0.8923 |
| No log | 3.0 | 117 | 0.3275 | 0.6826 | 0.6477 | 0.6647 | 0.8940 |
### Framework versions
- Transformers 4.33.0
- Pytorch 2.0.1
- Datasets 2.14.5
- Tokenizers 0.13.3
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