|
--- |
|
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 |
|
|
