---
license: mit
tags:
- generated_from_trainer
datasets:
- generator
model-index:
- name: gpt2-dp-2
  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-2

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: 4.3038

## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 9
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 6.5574        | 0.53  | 500  | 5.4160          |
| 5.0689        | 1.07  | 1000 | 4.9377          |
| 4.6601        | 1.6   | 1500 | 4.6589          |
| 4.3967        | 2.14  | 2000 | 4.4999          |
| 4.1846        | 2.67  | 2500 | 4.3930          |
| 4.0257        | 3.21  | 3000 | 4.3408          |
| 3.8965        | 3.74  | 3500 | 4.2798          |
| 3.7483        | 4.27  | 4000 | 4.2719          |
| 3.6522        | 4.81  | 4500 | 4.2338          |
| 3.4715        | 5.34  | 5000 | 4.2545          |
| 3.4106        | 5.88  | 5500 | 4.2303          |
| 3.2009        | 6.41  | 6000 | 4.2659          |
| 3.1644        | 6.94  | 6500 | 4.2559          |
| 2.9753        | 7.48  | 7000 | 4.2917          |
| 2.9548        | 8.01  | 7500 | 4.2926          |
| 2.846         | 8.55  | 8000 | 4.3038          |


### Framework versions

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