Training complete

README.md

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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