Model save

README.md

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+---
+license: mit
+base_model: indolem/indobert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: indobert-base-uncased-twitter-indonesia-sarcastic
+  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. -->
+
+# indobert-base-uncased-twitter-indonesia-sarcastic
+
+This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4358
+- Accuracy: 0.8060
+- F1: 0.5738
+- Precision: 0.6364
+- Recall: 0.5224
+
+## 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: 1e-05
+- train_batch_size: 32
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- num_epochs: 100.0
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.5531        | 1.0   | 59   | 0.4977          | 0.7724   | 0.4078 | 0.5833    | 0.3134 |
+| 0.4992        | 2.0   | 118  | 0.4785          | 0.7724   | 0.3441 | 0.6154    | 0.2388 |
+| 0.44          | 3.0   | 177  | 0.4819          | 0.7799   | 0.3656 | 0.6538    | 0.2537 |
+| 0.3815        | 4.0   | 236  | 0.4524          | 0.8097   | 0.6623 | 0.5952    | 0.7463 |
+| 0.3104        | 5.0   | 295  | 0.4547          | 0.8172   | 0.5421 | 0.725     | 0.4328 |
+| 0.2592        | 6.0   | 354  | 0.4058          | 0.8172   | 0.5664 | 0.6957    | 0.4776 |
+| 0.2083        | 7.0   | 413  | 0.4358          | 0.8060   | 0.5738 | 0.6364    | 0.5224 |
+
+
+### Framework versions
+
+- Transformers 4.36.2
+- Pytorch 2.1.1+cu121
+- Datasets 2.15.0
+- Tokenizers 0.15.0

model.safetensors

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