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: koneksi_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. -->
+
+# koneksi_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: 0.4885
+- Accuracy: 0.8177
+- F1: 0.8087
+- Precision: 0.8916
+- Recall: 0.74
+
+## 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   | 96   | 0.4936          | 0.7760   | 0.7817 | 0.7938    | 0.77   |
+| No log        | 2.0   | 192  | 0.4885          | 0.8177   | 0.8087 | 0.8916    | 0.74   |
+| No log        | 3.0   | 288  | 0.6119          | 0.7552   | 0.7662 | 0.7624    | 0.77   |
+| No log        | 4.0   | 384  | 1.0256          | 0.7552   | 0.7314 | 0.8533    | 0.64   |
+| No log        | 5.0   | 480  | 1.2790          | 0.7604   | 0.7629 | 0.7872    | 0.74   |
+| 0.2515        | 6.0   | 576  | 1.3453          | 0.7656   | 0.7716 | 0.7835    | 0.76   |
+| 0.2515        | 7.0   | 672  | 1.4966          | 0.7708   | 0.7864 | 0.7642    | 0.81   |
+| 0.2515        | 8.0   | 768  | 1.4197          | 0.7708   | 0.7660 | 0.8182    | 0.72   |
+| 0.2515        | 9.0   | 864  | 1.5297          | 0.7760   | 0.7861 | 0.7822    | 0.79   |
+| 0.2515        | 10.0  | 960  | 1.5265          | 0.7708   | 0.78   | 0.78      | 0.78   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.15.0
+- Tokenizers 0.15.0

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