---
license: mit
tags:
- generated_from_trainer
datasets:
- generator
model-index:
- name: gpt2-dp-mod-datasets
  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-dp-mod-datasets

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1587

## 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: 64
- eval_batch_size: 64
- 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: 6
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 6.721         | 0.28  | 500   | 5.6661          |
| 5.3704        | 0.55  | 1000  | 5.2444          |
| 5.0331        | 0.83  | 1500  | 4.9898          |
| 4.784         | 1.1   | 2000  | 4.8409          |
| 4.6004        | 1.38  | 2500  | 4.7323          |
| 4.5032        | 1.65  | 3000  | 4.6355          |
| 4.4157        | 1.93  | 3500  | 4.5419          |
| 4.2123        | 2.2   | 4000  | 4.5062          |
| 4.1323        | 2.48  | 4500  | 4.4562          |
| 4.1086        | 2.75  | 5000  | 4.3991          |
| 4.0432        | 3.03  | 5500  | 4.3667          |
| 3.8085        | 3.3   | 6000  | 4.3636          |
| 3.8151        | 3.58  | 6500  | 4.3268          |
| 3.7855        | 3.85  | 7000  | 4.2969          |
| 3.6519        | 4.13  | 7500  | 4.3076          |
| 3.5149        | 4.4   | 8000  | 4.3007          |
| 3.5086        | 4.68  | 8500  | 4.2851          |
| 3.4995        | 4.95  | 9000  | 4.2743          |
| 3.3468        | 5.23  | 9500  | 4.2884          |
| 3.3143        | 5.5   | 10000 | 4.2904          |
| 3.3138        | 5.78  | 10500 | 4.2893          |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.11.0+cu113
- Datasets 2.13.0
- Tokenizers 0.13.3