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---
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
widget:
- text: >-
    Absolutely thrilled with my new wireless earbuds! The sound quality is
    exceptional, and they stay securely in my ears during workouts. Plus, the
    charging case is so convenient for on-the-go use.
- text: >-
    This coffee maker has truly simplified my mornings. It brews quickly and the
    programmable features allow me to wake up to the aroma of freshly brewed
    coffee. Plus, the sleek design looks great on my countertop.
- text: >-
    I'm impressed with the durability of this laptop backpack. It comfortably
    fits my 15-inch laptop, charger, and other essentials without feeling bulky.
    The USB charging port is a lifesaver for staying connected on the move.
- text: >-
    As someone who loves to cook, this chef's knife is a game-changer. The sharp
    blade effortlessly cuts through vegetables, meats, and herbs, making prep
    work a breeze. The ergonomic handle ensures comfort even during long
    chopping sessions.
- text: >-
    This smart thermostat has made managing my home's temperature a breeze. The
    intuitive app allows me to adjust settings remotely, and the energy-saving
    features have noticeably reduced my utility bills. Installation was also a
    breeze thanks to clear instructions.
model-index:
- name: gpt2-amazon-sentiment-classifier
  results: []
license: mit
datasets:
- McAuley-Lab/Amazon-Reviews-2023
language:
- en
library_name: transformers
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# gpt2-amazon-sentiment-classifier

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0320
- Accuracy: 0.9680
- F1: 0.9680

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results



### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2