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README.md

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+---
+language:
+- tr
+license: mit
+base_model: dbmdz/bert-base-turkish-cased
+datasets:
+- wikiann
+- tr
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-base-turkish-cased-None
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: wikiann
+      type: wikiann
+      args: default
+    metrics:
+    - name: precision
+      type: precision
+      value: 0.9026122547249308
+    - name: recall
+      type: recall
+      value: 0.9218096877305139
+    - name: f1
+      type: f1
+      value: 0.912109968979989
+    - name: accuracy
+      type: accuracy
+      value: 0.9604539478979423
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: tr
+      type: tr
+    metrics:
+    - name: precision
+      type: precision
+      value: 0.9026122547249308
+    - name: recall
+      type: recall
+      value: 0.9218096877305139
+    - name: f1
+      type: f1
+      value: 0.912109968979989
+    - name: accuracy
+      type: accuracy
+      value: 0.9604539478979423
+---
+
+<!-- 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-base-turkish-cased-None
+
+This model is a fine-tuned version of [dbmdz/bert-base-turkish-cased](https://huggingface.co/dbmdz/bert-base-turkish-cased) on the wikiann and the tr datasets.
+It achieves the following results on the evaluation set:
+- precision: 0.9026
+- recall: 0.9218
+- f1: 0.9121
+- accuracy: 0.9605
+
+## 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:
+- num_train_epochs: 5
+- train_batch_size: 16
+- eval_batch_size: 32
+- learning_rate: 2e-05
+- weight_decay_rate: 0.01
+- num_warmup_steps: 0
+- fp16: True
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2