Update README.md

README.md

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 # US_politicians_covid_skepticism
 
 This model is a fine-tuned version of [vinai/bertweet-covid19-base-uncased](https://huggingface.co/vinai/bertweet-covid19-base-uncased) on an unknown dataset.
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+The model is intended to identify skepticism of COVID-19 policies (i.e. masks, social distancing, lockdowns, vaccines etc.) from US legislators. The model is training on 10k handcoded tweets. The model classifies as 1 (expressing skepticism/opposition to a COVID-19 policy or 0 (no opposition)
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 It achieves the following results on the evaluation set:
 - Train Loss: 0.1007
 - Train Sparse Categorical Accuracy: 0.9591
 - Validation Loss: 0.0913
 - Validation Sparse Categorical Accuracy: 0.9627
 - Epoch: 3
-The model is intended to identify skepticism of COVID-19 policies (i.e. masks, social distancing, lockdowns, vaccines etc.) from US legislators. The model is training on 10k handcoded tweets. The model classifies as 1 (expressing skepticism/opposition to a COVID-19 policy or 0 (no opposition)
-## Model description
-
-More information needed
-
-## Intended uses & limitations
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-More information needed
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-## Training and evaluation data
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-More information needed
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-## Training procedure
 
-### Training hyperparameters
 
 The following hyperparameters were used during training:
 - optimizer: {'name': 'Adam', 'learning_rate': 5e-07, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}