Indonesian Sarcasm Detection
Collection
D. Suhartono, W. Wongso and A. T. Handoyo, "IdSarcasm: Benchmarking and Evaluating Language Models for Indonesian Sarcasm Detection," in IEEE Access. • 14 items • Updated • 1
How to use w11wo/indobert-base-p1-reddit-indonesia-sarcastic with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="w11wo/indobert-base-p1-reddit-indonesia-sarcastic") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("w11wo/indobert-base-p1-reddit-indonesia-sarcastic")
model = AutoModelForSequenceClassification.from_pretrained("w11wo/indobert-base-p1-reddit-indonesia-sarcastic")This model is a fine-tuned version of indobenchmark/indobert-base-p1 on an unknown dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.4385 | 1.0 | 309 | 0.4258 | 0.7980 | 0.5675 | 0.6111 | 0.5297 |
| 0.3451 | 2.0 | 618 | 0.4345 | 0.8030 | 0.6283 | 0.5949 | 0.6657 |
| 0.2404 | 3.0 | 927 | 0.5054 | 0.8016 | 0.5318 | 0.6490 | 0.4504 |
| 0.1326 | 4.0 | 1236 | 0.7033 | 0.7860 | 0.5452 | 0.5820 | 0.5127 |
| 0.0787 | 5.0 | 1545 | 0.9796 | 0.7881 | 0.5335 | 0.5938 | 0.4844 |
Base model
indobenchmark/indobert-base-p1