End of training

README.md

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+---
+license: mit
+base_model: indobenchmark/indobert-base-p2
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: fitur_model
+  results: []
+---
+
+<!-- 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. -->
+
+# fitur_model
+
+This model is a fine-tuned version of [indobenchmark/indobert-base-p2](https://huggingface.co/indobenchmark/indobert-base-p2) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4122
+- Accuracy: 0.8077
+- F1: 0.8789
+- Precision: 0.8355
+- Recall: 0.9270
+
+## 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
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| No log        | 1.0   | 92   | 0.4122          | 0.8077   | 0.8789 | 0.8355    | 0.9270 |
+| No log        | 2.0   | 184  | 0.4881          | 0.8022   | 0.8657 | 0.8855    | 0.8467 |
+| No log        | 3.0   | 276  | 0.6448          | 0.8297   | 0.8912 | 0.8581    | 0.9270 |
+| No log        | 4.0   | 368  | 0.8912          | 0.8132   | 0.8786 | 0.8601    | 0.8978 |
+| No log        | 5.0   | 460  | 1.2147          | 0.7967   | 0.8702 | 0.8378    | 0.9051 |
+| 0.1904        | 6.0   | 552  | 1.3269          | 0.8077   | 0.8754 | 0.8542    | 0.8978 |
+| 0.1904        | 7.0   | 644  | 1.4276          | 0.7967   | 0.8693 | 0.8425    | 0.8978 |
+| 0.1904        | 8.0   | 736  | 1.4681          | 0.8022   | 0.8732 | 0.8435    | 0.9051 |
+| 0.1904        | 9.0   | 828  | 1.4804          | 0.7967   | 0.8693 | 0.8425    | 0.8978 |
+| 0.1904        | 10.0  | 920  | 1.4867          | 0.8022   | 0.8732 | 0.8435    | 0.9051 |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.15.0
+- Tokenizers 0.15.0

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