---
license: mit
base_model: gpt2
tags:
- generated_from_trainer
datasets:
- wiki_qa
model-index:
- name: output
  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. -->

# output

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the wiki_qa dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8781

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.9106        | 0.08  | 200  | 0.7699          |
| 0.9505        | 0.16  | 400  | 0.6965          |
| 0.8446        | 0.24  | 600  | 0.7000          |
| 0.8765        | 0.31  | 800  | 0.6573          |
| 0.7792        | 0.39  | 1000 | 0.7359          |
| 0.9293        | 0.47  | 1200 | 0.6926          |
| 0.9715        | 0.55  | 1400 | 0.7032          |
| 0.8898        | 0.63  | 1600 | 0.7208          |
| 1.0288        | 0.71  | 1800 | 0.6954          |
| 0.7782        | 0.79  | 2000 | 0.6629          |
| 0.9419        | 0.86  | 2200 | 0.7061          |
| 0.7138        | 0.94  | 2400 | 0.7086          |
| 0.9334        | 1.02  | 2600 | 0.6752          |
| 0.9274        | 1.1   | 2800 | 0.7142          |
| 0.7217        | 1.18  | 3000 | 0.7227          |
| 0.74          | 1.26  | 3200 | 0.6896          |
| 0.9408        | 1.34  | 3400 | 0.7039          |
| 0.8503        | 1.41  | 3600 | 0.7456          |
| 0.8816        | 1.49  | 3800 | 0.7226          |
| 0.7751        | 1.57  | 4000 | 0.7182          |
| 0.8669        | 1.65  | 4200 | 0.6904          |
| 1.059         | 1.73  | 4400 | 0.7131          |
| 0.8442        | 1.81  | 4600 | 0.7063          |
| 0.9162        | 1.89  | 4800 | 0.7128          |
| 0.9022        | 1.96  | 5000 | 0.7249          |
| 0.9427        | 2.04  | 5200 | 0.7333          |
| 0.9122        | 2.12  | 5400 | 0.6852          |
| 0.8159        | 2.2   | 5600 | 0.6950          |
| 0.9489        | 2.28  | 5800 | 0.7137          |
| 0.9976        | 2.36  | 6000 | 0.7101          |
| 0.9305        | 2.44  | 6200 | 0.7059          |
| 0.6405        | 2.51  | 6400 | 0.7167          |
| 0.9515        | 2.59  | 6600 | 0.6875          |
| 0.7186        | 2.67  | 6800 | 0.7057          |
| 0.9221        | 2.75  | 7000 | 0.6805          |
| 0.9118        | 2.83  | 7200 | 0.7011          |
| 0.9784        | 2.91  | 7400 | 0.6936          |
| 0.7532        | 2.99  | 7600 | 0.7046          |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3