update model card README.md

README.md

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+---
+tags:
+- generated_from_trainer
+datasets:
+- wikiann
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: BERT_swedish-ner
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: wikiann
+      type: wikiann
+      config: sv
+      split: train
+      args: sv
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.9340386115444618
+    - name: Recall
+      type: recall
+      value: 0.9418907624993855
+    - name: F1
+      type: f1
+      value: 0.9379482534942355
+    - name: Accuracy
+      type: accuracy
+      value: 0.979997105690534
+---
+
+<!-- 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. -->
+
+# BERT_swedish-ner
+
+This model is a fine-tuned version of [KB/bert-base-swedish-cased](https://huggingface.co/KB/bert-base-swedish-cased) on the wikiann dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1316
+- Precision: 0.9340
+- Recall: 0.9419
+- F1: 0.9379
+- Accuracy: 0.9800
+
+## 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: 5e-05
+- train_batch_size: 12
+- eval_batch_size: 12
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.22.1
+- Pytorch 1.12.1+cu113
+- Datasets 2.4.0
+- Tokenizers 0.12.1