End of training

README.md

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+---
+library_name: transformers
+license: mit
+base_model: indobenchmark/indobert-base-p1
+tags:
+- generated_from_trainer
+datasets:
+- indonlu
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: Model_analisis_sentimen
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: indonlu
+      type: indonlu
+      config: smsa
+      split: validation
+      args: smsa
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9412698412698413
+    - name: Precision
+      type: precision
+      value: 0.9167407809931684
+    - name: Recall
+      type: recall
+      value: 0.9068353459620502
+    - name: F1
+      type: f1
+      value: 0.9115530488925131
+---
+
+<!-- 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. -->
+
+# Model_analisis_sentimen
+
+This model is a fine-tuned version of [indobenchmark/indobert-base-p1](https://huggingface.co/indobenchmark/indobert-base-p1) on the indonlu dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4175
+- Accuracy: 0.9413
+- Precision: 0.9167
+- Recall: 0.9068
+- F1: 0.9116
+
+## 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: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Datasets 3.0.1
+- Tokenizers 0.19.1

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