End of training

README.md

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+---
+license: mit
+base_model: indolem/indobert-base-uncased
+tags:
+- generated_from_trainer
+model-index:
+- name: text-classification
+  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. -->
+
+# text-classification
+
+This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9868
+- Balanced Accuracy: 0.5178
+
+## 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: 5e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- 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 | Balanced Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:-----------------:|
+| 1.5005        | 1.0   | 75   | 1.2434          | 0.3803            |
+| 1.0016        | 2.0   | 150  | 1.1184          | 0.4835            |
+| 0.9022        | 3.0   | 225  | 1.0876          | 0.4952            |
+| 0.5408        | 4.0   | 300  | 0.9868          | 0.5178            |
+| 0.5569        | 5.0   | 375  | 1.0562          | 0.5062            |
+| 0.3193        | 6.0   | 450  | 1.1570          | 0.5065            |
+| 0.2545        | 7.0   | 525  | 1.2337          | 0.5328            |
+| 0.2079        | 8.0   | 600  | 1.2565          | 0.5404            |
+| 0.2004        | 9.0   | 675  | 1.3088          | 0.5403            |
+| 0.1072        | 10.0  | 750  | 1.3097          | 0.5498            |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.2
+- Tokenizers 0.19.1

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