End of training

README.md

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+---
+license: mit
+base_model: LazarusNLP/NusaBERT-base
+tags:
+- generated_from_trainer
+datasets:
+- indonlu
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: NusaBERT-base-POSP
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: indonlu
+      type: indonlu
+      config: posp
+      split: validation
+      args: posp
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.9577443609022557
+    - name: Recall
+      type: recall
+      value: 0.9577443609022557
+    - name: F1
+      type: f1
+      value: 0.9577443609022557
+    - name: Accuracy
+      type: accuracy
+      value: 0.9577443609022557
+---
+
+<!-- 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-base-POSP
+
+This model is a fine-tuned version of [LazarusNLP/NusaBERT-base](https://huggingface.co/LazarusNLP/NusaBERT-base) on the indonlu dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1472
+- Precision: 0.9577
+- Recall: 0.9577
+- F1: 0.9577
+- Accuracy: 0.9577
+
+## 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: 16
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 420  | 0.2680          | 0.9203    | 0.9203 | 0.9203 | 0.9203   |
+| 0.6283        | 2.0   | 840  | 0.2017          | 0.9379    | 0.9379 | 0.9379 | 0.9379   |
+| 0.218         | 3.0   | 1260 | 0.1785          | 0.9449    | 0.9449 | 0.9449 | 0.9449   |
+| 0.1612        | 4.0   | 1680 | 0.1692          | 0.9490    | 0.9490 | 0.9490 | 0.9490   |
+| 0.1393        | 5.0   | 2100 | 0.1577          | 0.9511    | 0.9511 | 0.9511 | 0.9511   |
+| 0.1119        | 6.0   | 2520 | 0.1503          | 0.9539    | 0.9539 | 0.9539 | 0.9539   |
+| 0.1119        | 7.0   | 2940 | 0.1499          | 0.9549    | 0.9549 | 0.9549 | 0.9549   |
+| 0.0943        | 8.0   | 3360 | 0.1542          | 0.9547    | 0.9547 | 0.9547 | 0.9547   |
+| 0.0824        | 9.0   | 3780 | 0.1517          | 0.9558    | 0.9558 | 0.9558 | 0.9558   |
+| 0.0785        | 10.0  | 4200 | 0.1519          | 0.9557    | 0.9557 | 0.9557 | 0.9557   |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.2.0+cu118
+- Datasets 2.17.1
+- Tokenizers 0.15.1

runs/Feb23_03-39-48_bookbot-h100/events.out.tfevents.1708659589.bookbot-h100.452679.0

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