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End of training
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README.md
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---
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license: mit
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base_model: indolem/indobert-base-uncased
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tags:
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- generated_from_trainer
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model-index:
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- name: ROS-text-classification
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# ROS-text-classification
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This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8096
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- Balanced Accuracy: 0.7524
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Balanced Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:-----------------:|
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| 1.4134 | 1.0 | 139 | 1.2061 | 0.5871 |
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| 0.7846 | 2.0 | 278 | 0.9400 | 0.6932 |
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| 0.6999 | 3.0 | 417 | 0.8096 | 0.7524 |
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| 0.3644 | 4.0 | 556 | 0.8431 | 0.7721 |
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| 0.3832 | 5.0 | 695 | 0.9038 | 0.7594 |
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| 0.2631 | 6.0 | 834 | 1.0126 | 0.7800 |
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### Framework versions
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- Transformers 4.41.2
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- Pytorch 2.3.0+cu121
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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model.safetensors
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