--- license: mit base_model: roberta-base tags: - generated_from_trainer metrics: - accuracy - precision - recall - f1 model-index: - name: irony_it_Italy results: [] --- # irony_it_Italy This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on part of the MultiPICo dataset. It achieves the following results on the evaluation set: - Loss: 0.0025 - Accuracy: 0.6653 - Precision: 0.4091 - Recall: 0.7377 - F1: 0.5263 ## Model description The model is trained considering the annotation of annotators from Italy only, on the French instances. The Italian annotations from these annotators are aggregated using majority voting and then used to train the model. ## Training and evaluation data The model has been trained on the annotation from annotators from Italy from the MultiPICo dataset. The data has been randomly split into a train and a validation set. ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-06 - train_batch_size: 16 - eval_batch_size: 64 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 20 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| | 0.0046 | 1.0 | 46 | 0.0043 | 0.4256 | 0.2759 | 0.7869 | 0.4085 | | 0.0043 | 2.0 | 92 | 0.0042 | 0.5579 | 0.3083 | 0.6066 | 0.4088 | | 0.0042 | 3.0 | 138 | 0.0041 | 0.5785 | 0.3084 | 0.5410 | 0.3929 | | 0.0039 | 4.0 | 184 | 0.0039 | 0.5041 | 0.3072 | 0.7705 | 0.4393 | | 0.0036 | 5.0 | 230 | 0.0036 | 0.5537 | 0.3309 | 0.7541 | 0.46 | | 0.0032 | 6.0 | 276 | 0.0032 | 0.6281 | 0.3802 | 0.7541 | 0.5055 | | 0.0025 | 7.0 | 322 | 0.0028 | 0.6777 | 0.4190 | 0.7213 | 0.5301 | | 0.0019 | 8.0 | 368 | 0.0023 | 0.6033 | 0.3684 | 0.8033 | 0.5052 | | 0.0016 | 9.0 | 414 | 0.0023 | 0.6074 | 0.3712 | 0.8033 | 0.5078 | | 0.0014 | 10.0 | 460 | 0.0025 | 0.6653 | 0.4091 | 0.7377 | 0.5263 | ### Framework versions - Transformers 4.34.1 - Pytorch 2.0.1+cu117 - Datasets 2.14.5 - Tokenizers 0.14.1