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: event_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. -->
+
+# event_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: 0.3165
+- Accuracy: 0.8491
+- F1: 0.8947
+- Precision: 0.8947
+- Recall: 0.8947
+
+## 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   | 27   | 0.3612          | 0.8302   | 0.8696 | 0.9677    | 0.7895 |
+| No log        | 2.0   | 54   | 0.3165          | 0.8491   | 0.8947 | 0.8947    | 0.8947 |
+| No log        | 3.0   | 81   | 0.3423          | 0.8679   | 0.9091 | 0.8974    | 0.9211 |
+| No log        | 4.0   | 108  | 0.4692          | 0.8302   | 0.88   | 0.8919    | 0.8684 |
+| No log        | 5.0   | 135  | 0.5180          | 0.8868   | 0.9189 | 0.9444    | 0.8947 |
+| No log        | 6.0   | 162  | 0.5619          | 0.8679   | 0.9041 | 0.9429    | 0.8684 |
+| No log        | 7.0   | 189  | 0.5528          | 0.8868   | 0.9189 | 0.9444    | 0.8947 |
+| No log        | 8.0   | 216  | 0.6213          | 0.8679   | 0.9041 | 0.9429    | 0.8684 |
+| No log        | 9.0   | 243  | 0.6155          | 0.8679   | 0.9041 | 0.9429    | 0.8684 |
+| No log        | 10.0  | 270  | 0.6123          | 0.8679   | 0.9041 | 0.9429    | 0.8684 |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.15.0
+- Tokenizers 0.15.0

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