Model save

README.md

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+---
+license: mit
+base_model: xlm-roberta-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: xlm-roberta-base-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. -->
+
+# xlm-roberta-base-twitter-indonesia-sarcastic
+
+This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7134
+- Accuracy: 0.8843
+- F1: 0.7634
+- Precision: 0.7812
+- Recall: 0.7463
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.5641        | 1.0   | 59   | 0.5260          | 0.75     | 0.0    | 0.0       | 0.0    |
+| 0.5317        | 2.0   | 118  | 0.5030          | 0.75     | 0.0    | 0.0       | 0.0    |
+| 0.4995        | 3.0   | 177  | 0.4656          | 0.75     | 0.0    | 0.0       | 0.0    |
+| 0.4599        | 4.0   | 236  | 0.4503          | 0.7687   | 0.6026 | 0.5281    | 0.7015 |
+| 0.4082        | 5.0   | 295  | 0.3785          | 0.8470   | 0.6435 | 0.7708    | 0.5522 |
+| 0.3274        | 6.0   | 354  | 0.3605          | 0.8619   | 0.6992 | 0.7679    | 0.6418 |
+| 0.2621        | 7.0   | 413  | 0.3765          | 0.8619   | 0.6838 | 0.8       | 0.5970 |
+| 0.2332        | 8.0   | 472  | 0.3408          | 0.8769   | 0.7591 | 0.7429    | 0.7761 |
+| 0.1579        | 9.0   | 531  | 0.4382          | 0.8731   | 0.7213 | 0.8       | 0.6567 |
+| 0.1467        | 10.0  | 590  | 0.3855          | 0.8806   | 0.7895 | 0.7059    | 0.8955 |
+| 0.098         | 11.0  | 649  | 0.4693          | 0.8806   | 0.7500 | 0.7869    | 0.7164 |
+| 0.0929        | 12.0  | 708  | 0.6206          | 0.8806   | 0.7333 | 0.8302    | 0.6567 |
+| 0.0555        | 13.0  | 767  | 0.7134          | 0.8843   | 0.7634 | 0.7812    | 0.7463 |
+
+
+### 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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