metadata
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner_swedish_small_set_health_and_prices
results: []
bert-finetuned-ner_swedish_small_set_health_and_prices
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: 0.0942
- Precision: 0.7709
- Recall: 0.8118
- F1: 0.7908
- Accuracy: 0.9741
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 | 250 | 0.1310 | 0.6116 | 0.7471 | 0.6726 | 0.9578 |
| 0.1583 | 2.0 | 500 | 0.0939 | 0.7560 | 0.8020 | 0.7783 | 0.9737 |
| 0.1583 | 3.0 | 750 | 0.0942 | 0.7709 | 0.8118 | 0.7908 | 0.9741 |
Framework versions
- Transformers 4.19.3
- Pytorch 1.7.1
- Datasets 2.2.2
- Tokenizers 0.12.1