Model save

README.md

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+---
+license: mit
+base_model: ayameRushia/roberta-base-indonesian-sentiment-analysis-smsa
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: roberta-stunting-medsos-sentiment
+  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. -->
+
+# roberta-stunting-medsos-sentiment
+
+This model is a fine-tuned version of [ayameRushia/roberta-base-indonesian-sentiment-analysis-smsa](https://huggingface.co/ayameRushia/roberta-base-indonesian-sentiment-analysis-smsa) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8784
+- Accuracy: 0.8742
+- Precision: 0.8496
+- Recall: 0.8438
+- F1: 0.8441
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| No log        | 1.0   | 314  | 0.4554          | 0.8487   | 0.8401    | 0.7848 | 0.8018 |
+| 0.4659        | 2.0   | 628  | 0.5678          | 0.8567   | 0.8501    | 0.7946 | 0.8133 |
+| 0.4659        | 3.0   | 942  | 0.6851          | 0.8535   | 0.8278    | 0.8404 | 0.8247 |
+| 0.1838        | 4.0   | 1256 | 0.8474          | 0.8742   | 0.8476    | 0.8470 | 0.8451 |
+| 0.0176        | 5.0   | 1570 | 0.8784          | 0.8742   | 0.8496    | 0.8438 | 0.8441 |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.1.2
+- Datasets 2.19.2
+- Tokenizers 0.19.1

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