# Harsh Deep Pandey: Open-Weight Models and Datasets
Source: https://savrn.com/model-publishers/harshdpandey
Markdown alternate of the page above; the site index is https://savrn.com/llms.txt

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## Models

Model · Text classification

### [food_not_food_text_classifier](https://savrn.com/models/food-not-food-text-classifier)

[Harsh Deep Pandey](https://savrn.com/model-publishers/harshdpandey)

This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set: The following hyperparameters were used during training: - learningrate: 0.0001 - trainbatchsize: 32 - evalbatchsize: 32 - lrschedulertype: linear - numepochs: 10 - Transformers 5.17.0 - Pytorch 2.11.0+cu130 - Datasets 5.0.1 - Tokenizers 0.23.2

Open weights apache-2.0 67M parameters 512 tokens transformers

[View model](https://savrn.com/models/food-not-food-text-classifier)

## Explore More

- [All model publishers](https://savrn.com/model-publishers)
- [The model directory](https://savrn.com/models)
- [The dataset directory](https://savrn.com/datasets)

## Source

- Listed from their public repositories, read 2026-09-29.
- [Hugging Face profile](https://huggingface.co/harshdpandey)
- [How the hub is built](https://savrn.com/model-hub/methodology)