Text Classification
Transformers
PyTorch
TensorBoard
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use coderSounak/finetuned_twitter_sentiment_roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use coderSounak/finetuned_twitter_sentiment_roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="coderSounak/finetuned_twitter_sentiment_roberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("coderSounak/finetuned_twitter_sentiment_roberta") model = AutoModelForSequenceClassification.from_pretrained("coderSounak/finetuned_twitter_sentiment_roberta") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): 1fd02f0
update model card README.md
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README.md
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# finetuned_twitter_sentiment_roberta
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This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment
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It achieves the following results on the evaluation set:
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- Loss: 1.
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- Accuracy: 0.
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- F1: 0.
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- Precision: 0.
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- Recall: 0.
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## Model description
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# finetuned_twitter_sentiment_roberta
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This model is a fine-tuned version of [cardiffnlp/twitter-xlm-roberta-base-sentiment](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base-sentiment) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.3361
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- Accuracy: 0.7419
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- F1: 0.7411
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- Precision: 0.7419
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- Recall: 0.7419
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## Model description
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