metadata
license: mit
base_model: xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: XLM_RoBERTa-Multilingual-Clickbait-Detection
results: []
datasets:
- christinacdl/clickbait_detection_dataset
language:
- en
- el
- it
- es
- pt
- pl
- ro
- de
pipeline_tag: text-classification
XLM_RoBERTa-Multilingual-Clickbait-Detection
This model is a fine-tuned version of xlm-roberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2346
- Micro F1: 0.9735
- Macro F1: 0.9734
- Accuracy: 0.9735
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
Framework versions
- Transformers 4.36.1
- Pytorch 2.1.0+cu121
- Datasets 2.13.1
- Tokenizers 0.15.0