---
license: mit
tags:
- generated_from_trainer
datasets:
- generator
model-index:
- name: gpt2-dp-guten-rarity-all-5k-2p5k
  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-guten-rarity-all-5k-2p5k

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: 4.3172

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 6.6951        | 0.28  | 500   | 5.6610          |
| 5.3498        | 0.55  | 1000  | 5.2276          |
| 5.0115        | 0.83  | 1500  | 4.9818          |
| 4.7688        | 1.1   | 2000  | 4.8256          |
| 4.5712        | 1.38  | 2500  | 4.7126          |
| 4.4784        | 1.65  | 3000  | 4.6078          |
| 4.3906        | 1.93  | 3500  | 4.5226          |
| 4.1804        | 2.21  | 4000  | 4.4857          |
| 4.1213        | 2.48  | 4500  | 4.4278          |
| 4.0805        | 2.76  | 5000  | 4.3689          |
| 4.0172        | 3.03  | 5500  | 4.3318          |
| 3.7877        | 3.31  | 6000  | 4.3246          |
| 3.7896        | 3.58  | 6500  | 4.2902          |
| 3.7714        | 3.86  | 7000  | 4.2610          |
| 3.628         | 4.13  | 7500  | 4.2685          |
| 3.4948        | 4.41  | 8000  | 4.2600          |
| 3.4897        | 4.69  | 8500  | 4.2447          |
| 3.4837        | 4.96  | 9000  | 4.2332          |
| 3.327         | 5.24  | 9500  | 4.2460          |
| 3.2974        | 5.51  | 10000 | 4.2442          |
| 3.296         | 5.79  | 10500 | 4.2437          |


### Framework versions

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