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--- |
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license: apache-2.0 |
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datasets: |
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- andrea-t94/TwitterSentiment140 |
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language: |
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- en |
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metrics: |
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- perplexity |
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library_name: transformers |
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tags: |
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- distillroberta-base |
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- twitter |
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pipeline_tag: fill-mask |
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--- |
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## Twitter-roBERTa-base fine-tuned using masked language modelling |
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This is a RoBERTa-base model finetuned (domain adaptation) on ~2M tweets from Jin 2009 (sentiment140). |
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This is the first step of a two steps approach to finetune for sentiment analysis (ULMFit) |
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This model is suitable for English. |
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Main charachetistics: |
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- pretrained model and tokenizer: distillroberta-base |
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- no cleaning/processing applied to the data |
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Reference Paper: [ULMFit](https://arxiv.org/abs/1801.06146). |
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Reference dataset: [Sentiment140](https://www.kaggle.com/datasets/kazanova/sentiment140?resource=download) |
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Git Repo: TBD |
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Labels: 0 -> Negative; 1 -> Positive |
