metadata
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner_swedish_test
results: []
bert-finetuned-ner_swedish_test
This model is a fine-tuned version of KBLab/bert-base-swedish-cased-ner on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0916
- Precision: 0.6835
- Recall: 0.6391
- F1: 0.6606
- Accuracy: 0.9788
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 | 128 | 0.0980 | 0.6121 | 0.5976 | 0.6048 | 0.9749 |
| No log | 2.0 | 256 | 0.0914 | 0.7255 | 0.6568 | 0.6894 | 0.9779 |
| No log | 3.0 | 384 | 0.0916 | 0.6835 | 0.6391 | 0.6606 | 0.9788 |
Framework versions
- Transformers 4.19.3
- Pytorch 1.7.1
- Datasets 2.2.2
- Tokenizers 0.12.1