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--- |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: bert-finetuned-ner_swedish_small_set_health_and_prices |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# bert-finetuned-ner_swedish_small_set_health_and_prices |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0942 |
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- Precision: 0.7709 |
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- Recall: 0.8118 |
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- F1: 0.7908 |
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- Accuracy: 0.9741 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 250 | 0.1310 | 0.6116 | 0.7471 | 0.6726 | 0.9578 | |
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| 0.1583 | 2.0 | 500 | 0.0939 | 0.7560 | 0.8020 | 0.7783 | 0.9737 | |
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| 0.1583 | 3.0 | 750 | 0.0942 | 0.7709 | 0.8118 | 0.7908 | 0.9741 | |
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### Framework versions |
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- Transformers 4.19.3 |
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- Pytorch 1.7.1 |
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- Datasets 2.2.2 |
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- Tokenizers 0.12.1 |
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