---
language:
- en
library_name: transformers
pipeline_tag: text-classification
tags:
- multi-nli
- bert
---
# Model Card for Model ID

<!-- Provide a quick summary of what the model is/does. -->

This is a BERT model fine-tuned on [multi_nli](https://huggingface.co/datasets/multi_nli) dataset.

## Model Details

### Model Description

<!-- Provide a longer summary of what this model is. -->


- **Developed by:** nouf-sst.
- **Model type:** Transformer.
- **Language(s) (NLP):** English.
- **Finetuned from model [optional]:** BERT.


## Bias, Risks, and Limitations

<!-- This section is meant to convey both technical and sociotechnical limitations. -->

The model is finetuned on subset of multi_nli dataset (i.e., 50000 samples).


## How to Get Started with the Model

Use the code below to get started with the model.

[More Information Needed]

## Training Details

### Training Data

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[More Information Needed]

### Training Procedure 

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#### Preprocessing [optional]

[More Information Needed]


#### Training Hyperparameters

- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->

#### Speeds, Sizes, Times [optional]

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[More Information Needed]

## Evaluation

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### Testing Data, Factors & Metrics

#### Testing Data

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[More Information Needed]

#### Factors

<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->

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#### Metrics

<!-- These are the evaluation metrics being used, ideally with a description of why. -->

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### Results

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#### Summary


## Citation [optional]

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**BibTeX:**

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**APA:**

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