Text Classification
Transformers
PyTorch
English
bert
Generated from Trainer
bert-base-uncased
fp32
Eval Results (legacy)
text-embeddings-inference
Instructions to use Intel/bert-base-uncased-mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Intel/bert-base-uncased-mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Intel/bert-base-uncased-mrpc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Intel/bert-base-uncased-mrpc") model = AutoModelForSequenceClassification.from_pretrained("Intel/bert-base-uncased-mrpc") - Inference
- Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-base-uncased-
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the GLUE MRPC dataset.
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It achieves the following results on the evaluation set:
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- F1: 0.9042
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- Combined Score: 0.8822
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## Model description
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More information needed
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## 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
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### Training hyperparameters
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The following hyperparameters were used during training:
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- lr_scheduler_type: linear
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- num_epochs: 5.0
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### Training results
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### Framework versions
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- Transformers 4.17.0
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-base-uncased-mrpc
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the GLUE MRPC dataset.
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It achieves the following results on the evaluation set:
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- F1: 0.9042
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- Combined Score: 0.8822
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### Training hyperparameters
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The following hyperparameters were used during training:
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- lr_scheduler_type: linear
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- num_epochs: 5.0
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### Framework versions
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- Transformers 4.17.0
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