Arabic-Handwritten-Images-Recognition
A deep learning model to classify the Arabic letters and digits easily. (by AmrHendy)
iSarcasmEval
Datasets used for iSarcasmEval shared-task (Task 6 at SemEval 2022) (by iabufarha)
Arabic-Handwritten-Images-Recognition | iSarcasmEval | |
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1 | 1 | |
50 | 19 | |
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0.0 | 10.0 | |
almost 4 years ago | over 1 year ago | |
Jupyter Notebook | ||
MIT License | MIT License |
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Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Arabic-Handwritten-Images-Recognition
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iSarcasmEval
Posts with mentions or reviews of iSarcasmEval.
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Fine-tuned model consistently producing Precision and Recall scores of 0 from start of training, any suggestions on how to improve?
The labels are extracted and put into their own df which is then fed alongside the text data as tensors to the model. The observations for each class are fairly low due to it being a small but thorough dataset defined and labelled specifically for these tasks, so I can't really change it. However I have been wondering whether I should just generally train the model on sarcasm detection first using a Kaggle dataset or something, then fine tuning again for this subtask (B in the link).
What are some alternatives?
When comparing Arabic-Handwritten-Images-Recognition and iSarcasmEval you can also consider the following projects:
fastai - The fastai deep learning library
pragmatapro - PragmataPro font is designed to help pros to work better
electra - ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators
BERTweet - BERTweet: A pre-trained language model for English Tweets (EMNLP-2020)
anees-dataset - The dataset used to fine-tune the GPT-2 model used in Anees for the multi-turn dialogue generation.