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--- |
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license: mit |
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base_model: roberta-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: irony_en_United_Kingdom |
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results: [] |
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--- |
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# irony_en_United_Kingdom |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on part of the [EPIC](https://huggingface.co/datasets/Multilingual-Perspectivist-NLU/EPIC) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0023 |
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- Accuracy: 0.6833 |
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- Precision: 0.4764 |
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- Recall: 0.7339 |
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- F1: 0.5778 |
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## Model description |
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The model is trained considering the annotation of annotators from the United Kingdom only. |
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The annotations from these annotators are aggregated using majority voting and then used to train the model. |
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## Training and evaluation data |
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The model has been trained on the annotation from annotators from the United Kingdom from the [EPIC](https://huggingface.co/datasets/Multilingual-Perspectivist-NLU/EPIC) dataset. |
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The data has been randomly split in a train and a validation set. |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-06 |
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- train_batch_size: 16 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 20 |
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- early stopping (patience: 2) |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 0.0044 | 1.0 | 79 | 0.0042 | 0.5310 | 0.3612 | 0.7661 | 0.4910 | |
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| 0.0043 | 2.0 | 158 | 0.0040 | 0.6595 | 0.4417 | 0.5806 | 0.5017 | |
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| 0.0039 | 3.0 | 237 | 0.0034 | 0.6310 | 0.4188 | 0.6452 | 0.5079 | |
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| 0.0033 | 4.0 | 316 | 0.0027 | 0.7286 | 0.5352 | 0.6129 | 0.5714 | |
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| 0.0022 | 5.0 | 395 | 0.0024 | 0.5833 | 0.4066 | 0.8952 | 0.5592 | |
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| 0.0015 | 6.0 | 474 | 0.0022 | 0.7357 | 0.5474 | 0.6048 | 0.5747 | |
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| 0.001 | 7.0 | 553 | 0.0022 | 0.7262 | 0.5302 | 0.6371 | 0.5788 | |
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| 0.0005 | 8.0 | 632 | 0.0023 | 0.6833 | 0.4764 | 0.7339 | 0.5778 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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