Text Classification
Transformers
TensorBoard
Safetensors
xlm-roberta
Trained with AutoTrain
text-embeddings-inference
Instructions to use Sathvik6323/cardiffnlp-twitter-roberta-base-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sathvik6323/cardiffnlp-twitter-roberta-base-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sathvik6323/cardiffnlp-twitter-roberta-base-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sathvik6323/cardiffnlp-twitter-roberta-base-sentiment") model = AutoModelForSequenceClassification.from_pretrained("Sathvik6323/cardiffnlp-twitter-roberta-base-sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model Trained Using AutoTrain
- Problem type: Text Classification
Validation Metrics
loss: 1.0112701654434204
f1_macro: 0.23304414883362254
f1_micro: 0.5374355326338254
f1_weighted: 0.37573861876678316
precision_macro: 0.17914517754460846
precision_micro: 0.5374355326338254
precision_weighted: 0.28883695173740354
recall_macro: 0.3333333333333333
recall_micro: 0.5374355326338254
recall_weighted: 0.5374355326338254
accuracy: 0.5374355326338254
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