Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
English
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use JeremiahZ/roberta-base-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JeremiahZ/roberta-base-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JeremiahZ/roberta-base-mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JeremiahZ/roberta-base-mnli") model = AutoModelForSequenceClassification.from_pretrained("JeremiahZ/roberta-base-mnli") - Notebooks
- Google Colab
- Kaggle
Jeremiah Zhou commited on
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Parent(s): 77c56c6
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README.md
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# roberta-base-mnli
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This model is a fine-tuned version of [
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It achieves the following results on the evaluation set:
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- eval_loss: 0.7539
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- eval_accuracy: 0.8697
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# roberta-base-mnli
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base/) on the GLUE MNLI dataset.
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It achieves the following results on the evaluation set:
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- eval_loss: 0.7539
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- eval_accuracy: 0.8697
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