---
base_model: gpt2
library_name: peft
license: mit
metrics:
- accuracy
- f1
- precision
- recall
tags:
- generated_from_trainer
model-index:
- name: gpt2-sst2-sentiment-classifier-lora
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# gpt2-sst2-sentiment-classifier-lora

This model is a fine-tuned version of [gpt2](https://huggingface.co./gpt2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2636
- Accuracy: 0.9083
- F1: 0.9111
- Precision: 0.8991
- Recall: 0.9234

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.3138        | 1.0   | 4210  | 0.2550          | 0.9014   | 0.9034 | 0.9013    | 0.9054 |
| 0.2597        | 2.0   | 8420  | 0.2666          | 0.9014   | 0.9061 | 0.8792    | 0.9347 |
| 0.2436        | 3.0   | 12630 | 0.2636          | 0.9083   | 0.9111 | 0.8991    | 0.9234 |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1