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---
base_model: openai-community/gpt2
library_name: peft
license: mit
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: GPT2-small-PEFT-LoRA-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
---
<!-- 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-small-PEFT-LoRA-finetuned-amazon-reviews-en-classification
This model is a fine-tuned version of [openai-community/gpt2](https://huggingface.co/openai-community/gpt2) on [mteb/amazon_reviews_multi](https://huggingface.co/datasets/mteb/amazon_reviews_multi) dataset.
It is the result of the post [Fine tunning SML](https://maximofn.com/lora/)
It achieves the following results on the evaluation set:
- Loss: 1.4127
- Accuracy: 0.3862
## 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: 400
- eval_batch_size: 400
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.2751 | 1.0 | 500 | 1.5125 | 0.3182 |
| 1.5159 | 2.0 | 1000 | 1.4176 | 0.3738 |
| 1.4635 | 3.0 | 1500 | 1.4051 | 0.3814 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.43.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |