Training complete

README.md

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+---
+library_name: transformers
+base_model: cahya/NusaBert-v0.5
+tags:
+- generated_from_trainer
+datasets:
+- conll2003
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: NusaBert-ner
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: conll2003
+      type: conll2003
+      config: conll2003
+      split: validation
+      args: conll2003
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.8695088344950559
+    - name: Recall
+      type: recall
+      value: 0.9027263547627061
+    - name: F1
+      type: f1
+      value: 0.885806291800842
+    - name: Accuracy
+      type: accuracy
+      value: 0.9798333197726454
+---
+
+<!-- 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. -->
+
+# NusaBert-ner
+
+This model is a fine-tuned version of [cahya/NusaBert-v0.5](https://huggingface.co/cahya/NusaBert-v0.5) on the conll2003 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1065
+- Precision: 0.8695
+- Recall: 0.9027
+- F1: 0.8858
+- Accuracy: 0.9798
+
+## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0988        | 1.0   | 1756 | 0.0918          | 0.8335    | 0.8701 | 0.8514 | 0.9732   |
+| 0.0313        | 2.0   | 3512 | 0.0973          | 0.8639    | 0.8950 | 0.8792 | 0.9778   |
+| 0.0083        | 3.0   | 5268 | 0.1065          | 0.8695    | 0.9027 | 0.8858 | 0.9798   |
+
+
+### Framework versions
+
+- Transformers 4.48.2
+- Pytorch 2.5.1+cu124
+- Datasets 3.2.0
+- Tokenizers 0.21.0

runs/Feb13_22-15-27_a18b65db8ae1/events.out.tfevents.1739484946.a18b65db8ae1.563.0

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