---
license: mit
base_model: gpt2
tags:
- generated_from_trainer
metrics:
- accuracy
library_name: peft
model-index:
- name: p-tuning-t2t-gpt2-large-with-sst2
  results: []
---

<!-- 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. -->

# p-tuning-t2t-gpt2-large-with-sst2

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: 0.4929
- Accuracy: 0.7741

## 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: 0.0001
- 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: cosine
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.6984        | 1.0   | 4210  | 0.7020          | 0.5138   |
| 0.6766        | 2.0   | 8420  | 0.6971          | 0.5138   |
| 0.5377        | 3.0   | 12630 | 0.5625          | 0.7087   |
| 0.5375        | 4.0   | 16840 | 0.5481          | 0.7282   |
| 0.5209        | 5.0   | 21050 | 0.5278          | 0.7420   |
| 0.5235        | 6.0   | 25260 | 0.5357          | 0.7374   |
| 0.5311        | 7.0   | 29470 | 0.5342          | 0.7294   |
| 0.5545        | 8.0   | 33680 | 0.5135          | 0.7511   |
| 0.5406        | 9.0   | 37890 | 0.5138          | 0.7397   |
| 0.523         | 10.0  | 42100 | 0.5192          | 0.7580   |
| 0.5248        | 11.0  | 46310 | 0.4997          | 0.7706   |
| 0.559         | 12.0  | 50520 | 0.5063          | 0.7649   |
| 0.582         | 13.0  | 54730 | 0.4958          | 0.7741   |
| 0.4796        | 14.0  | 58940 | 0.4981          | 0.7706   |
| 0.4173        | 15.0  | 63150 | 0.4911          | 0.7626   |
| 0.4449        | 16.0  | 67360 | 0.4932          | 0.7718   |
| 0.4697        | 17.0  | 71570 | 0.4917          | 0.7741   |
| 0.3779        | 18.0  | 75780 | 0.4931          | 0.7729   |
| 0.449         | 19.0  | 79990 | 0.4929          | 0.7729   |
| 0.4938        | 20.0  | 84200 | 0.4929          | 0.7741   |


### Framework versions

- PEFT 0.7.1
- Transformers 4.40.1
- Pytorch 2.5.0
- Datasets 3.0.1
- Tokenizers 0.19.1