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README.md
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model-index:
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- name: ernie-2.0-base-en-Tweet_About_Disaster_Or_Not
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# ernie-2.0-base-en-Tweet_About_Disaster_Or_Not
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This model is a fine-tuned version of [nghuyong/ernie-2.0-base-en](https://huggingface.co/nghuyong/ernie-2.0-base-en) on the None dataset.
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## Model description
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## Intended uses & limitations
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## Training and evaluation data
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## Training procedure
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- Transformers 4.26.1
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- Pytorch 1.13.1
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- Datasets 2.9.0
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- Tokenizers 0.12.1
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model-index:
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- name: ernie-2.0-base-en-Tweet_About_Disaster_Or_Not
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results: []
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language:
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- en
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# ernie-2.0-base-en-Tweet_About_Disaster_Or_Not
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This model is a fine-tuned version of [nghuyong/ernie-2.0-base-en](https://huggingface.co/nghuyong/ernie-2.0-base-en) on the None dataset.
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## Model description
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This is a binary classification model to determine if tweet input samples are about a disaster or not.
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For more information on how it was created, check out the following link: https://github.com/DunnBC22/NLP_Projects/blob/main/Binary%20Classification/Transformer%20Comparison/Is%20This%20Tweet%20Referring%20to%20a%20Disaster%20or%20Not%3F%20-%20ERNIE.ipynb
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### Associated Projects
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This project is part of a comparison of multiple transformers. The others can be found at the following links:
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- https://huggingface.co/DunnBC22/roberta-base-Tweet_About_Disaster_Or_Not
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- https://huggingface.co/DunnBC22/deberta-v3-small-Tweet_About_Disaster_Or_Not
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- https://huggingface.co/DunnBC22/albert-base-v2-Tweet_About_Disaster_Or_Not
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- https://huggingface.co/DunnBC22/electra-base-emotion-Tweet_About_Disaster_Or_Not
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- https://huggingface.co/DunnBC22/distilbert-base-uncased-Tweet_About_Disaster_Or_Not
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## Intended uses & limitations
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This model is intended to demonstrate my ability to solve a complex problem using technology.
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The main limitation is the quality of the data source.
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## Training and evaluation data
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Dataset Source: https://www.kaggle.com/datasets/vstepanenko/disaster-tweets
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## Training procedure
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- Transformers 4.26.1
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- Pytorch 1.13.1
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- Datasets 2.9.0
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- Tokenizers 0.12.1
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