metadata
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: irony_en_United_Kingdom
results: []
irony_en_United_Kingdom
This model is a fine-tuned version of roberta-base on part of the EPIC dataset. It achieves the following results on the evaluation set:
- Loss: 0.0023
- Accuracy: 0.6833
- Precision: 0.4764
- Recall: 0.7339
- F1: 0.5778
Model description
The model is trained considering the annotation of annotators from the United Kingdom only. The 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 the United Kingdom from the EPIC dataset. The data has been randomly split in 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
- early stopping (patience: 2)
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.0044 | 1.0 | 79 | 0.0042 | 0.5310 | 0.3612 | 0.7661 | 0.4910 |
| 0.0043 | 2.0 | 158 | 0.0040 | 0.6595 | 0.4417 | 0.5806 | 0.5017 |
| 0.0039 | 3.0 | 237 | 0.0034 | 0.6310 | 0.4188 | 0.6452 | 0.5079 |
| 0.0033 | 4.0 | 316 | 0.0027 | 0.7286 | 0.5352 | 0.6129 | 0.5714 |
| 0.0022 | 5.0 | 395 | 0.0024 | 0.5833 | 0.4066 | 0.8952 | 0.5592 |
| 0.0015 | 6.0 | 474 | 0.0022 | 0.7357 | 0.5474 | 0.6048 | 0.5747 |
| 0.001 | 7.0 | 553 | 0.0022 | 0.7262 | 0.5302 | 0.6371 | 0.5788 |
| 0.0005 | 8.0 | 632 | 0.0023 | 0.6833 | 0.4764 | 0.7339 | 0.5778 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.1