metadata

base_model: openai-community/gpt2
library_name: peft
license: mit
metrics:
  - accuracy
tags:
  - generated_from_trainer
model-index:
  - name: GPT2-small-QLoRA-finetuned-amazon-reviews-en-classification
    results: []
datasets:
  - mteb/amazon_reviews_multi
language:
  - en
widget:
  - text: It`s an amazing product
  - text: I hate this product
  - text: It's ok, but a bit expensive
pipeline_tag: text-classification

GPT2-small-QLoRA-finetuned-amazon-reviews-en-classification

This model is a fine-tuned version of openai-community/gpt2 on mteb/amazon_reviews_multi dataset.

It is the result of the post QLoRA

It achieves the following results on the evaluation set:

Loss: 0.8883
Accuracy: 0.615

Model description

This model provides classification of reviews in english

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: 224
eval_batch_size: 224
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
2.088	1.0	893	0.9780	0.5848
0.9588	2.0	1786	0.8940	0.6156
0.9147	3.0	2679	0.8918	0.6168

Framework versions

PEFT 0.12.0
Transformers 4.43.3
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1