Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use xshubhamx/roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xshubhamx/roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xshubhamx/roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("xshubhamx/roberta-base") model = AutoModelForSequenceClassification.from_pretrained("xshubhamx/roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload README.md with huggingface_hub
Browse files
README.md
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This model was trained from scratch on an unknown dataset.
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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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- Precision: 0.
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- Recall: 0.
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- Precision Macro: 0.7709
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- Recall Macro: 0.7766
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- Macro Fpr: 0.0161
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This model was trained from scratch on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.4985
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- Accuracy: 0.8156
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- Precision: 0.8163
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- Recall: 0.8156
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- Precision Macro: 0.7709
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- Recall Macro: 0.7766
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- Macro Fpr: 0.0161
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