pegahyaftian / spanemo

SpanEmo

SpanEmo

---

Source code for the paper "SpanEmo: Casting Multi-label Emotion Classification as Span-prediction" in EACL2021.

 

Dependencies

We used Python=3.6, torch=1.2.0. Other packages can be installed via:

pip install -r requirements.txt

The model was trained on an Nvidia GeForce GTX1080 with 11GB memory, Ubuntu 18.10.

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Usage

You first need to download the dataset Link for the language of your choice (i.e., English, Arabic or Spanish) and then place them in the data directory data/.

Next, run the main script to do the followings:

• data loading and preprocessing
• model creation and training

Training

python scripts/train.py --train-path {} --dev-path {}

Options:
    -h --help                         show this screen
    --loss-type=<str>                 which loss to use cross-ent|corr|joint. [default: cross-entropy]
    --max-length=<int>                text length [default: 128]
    --output-dropout=<float>          prob of dropout applied to the output layer [default: 0.1]
    --seed=<int>                      fixed random seed number [default: 42]
    --train-batch-size=<int>          batch size [default: 32]
    --eval-batch-size=<int>           batch size [default: 32]
    --max-epoch=<int>                 max epoch [default: 20]
    --ffn-lr=<float>                  ffn learning rate [default: 0.001]
    --bert-lr=<float>                 bert learning rate [default: 2e-5]
    --lang=<str>                      language choice [default: English]
    --dev-path=<str>                  file path of the dev set [default: '']
    --train-path=<str>                file path of the train set [default: '']
    --alpha-loss=<float>              weight used to balance the loss [default: 0.2]

Once the above step is done, you can then evaluate on the test set using the trained model:

Evaluation

python scripts/test.py --test-path {} --model-path {}

Options:
    -h --help                         show this screen
    --model-path=<str>                path of the trained model
    --max-length=<int>                text length [default: 128]
    --seed=<int>                      seed [default: 0]
    --test-batch-size=<int>           batch size [default: 32]
    --lang=<str>                      language choice [default: English]
    --test-path=<str>                 file path of the test set [default: ]

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Citation

Please cite the following paper if you found it useful. Thanks:)

@inproceedings{alhuzali-ananiadou-2021-spanemo,
    title = "{S}pan{E}mo: Casting Multi-label Emotion Classification as Span-prediction",
    author = "Alhuzali, Hassan  and
      Ananiadou, Sophia",
    booktitle = "Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume",
    month = apr,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/2021.eacl-main.135",
    pages = "1573--1584",
}