---
license: mit
base_model: gpt2
tags:
- generated_from_trainer
model-index:
- name: gpt2-alpaca-instruction-fine-tuning-qlora
  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. -->

# gpt2-alpaca-instruction-fine-tuning-qlora

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: 1.8330

## 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: 0.0005
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.1183        | 0.11  | 1000 | 1.8975          |
| 2.1329        | 0.22  | 2000 | 1.8818          |
| 2.1179        | 0.33  | 3000 | 1.8770          |
| 2.0949        | 0.44  | 4000 | 1.8662          |
| 2.0871        | 0.55  | 5000 | 1.8477          |
| 2.0668        | 0.66  | 6000 | 1.8447          |
| 2.0636        | 0.77  | 7000 | 1.8379          |
| 2.0442        | 0.88  | 8000 | 1.8311          |
| 2.0597        | 0.99  | 9000 | 1.8330          |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3