---
license: mit
tags:
- generated_from_trainer
datasets:
- generator
model-index:
- name: gpt2-concat-guten-rarity-iroder-est-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-concat-guten-rarity-iroder-est-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: 3.1825

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 6.7149        | 0.3   | 500   | 5.6379          |
| 5.3626        | 0.59  | 1000  | 5.2053          |
| 5.0103        | 0.89  | 1500  | 4.9561          |
| 4.7374        | 1.18  | 2000  | 4.8042          |
| 4.5794        | 1.48  | 2500  | 4.6786          |
| 4.4756        | 1.77  | 3000  | 4.5728          |
| 4.3345        | 2.07  | 3500  | 4.4966          |
| 4.1538        | 2.36  | 4000  | 4.4468          |
| 4.1275        | 2.66  | 4500  | 4.3875          |
| 4.0815        | 2.95  | 5000  | 4.3316          |
| 3.8534        | 3.25  | 5500  | 4.3293          |
| 3.8151        | 3.54  | 6000  | 4.2939          |
| 3.8069        | 3.84  | 6500  | 4.2572          |
| 3.6706        | 4.13  | 7000  | 4.2627          |
| 3.5322        | 4.43  | 7500  | 4.2534          |
| 3.5274        | 4.73  | 8000  | 4.2397          |
| 3.4978        | 5.02  | 8500  | 4.2343          |
| 3.3402        | 5.32  | 9000  | 4.2407          |
| 3.3342        | 5.61  | 9500  | 4.2388          |
| 3.3308        | 5.91  | 10000 | 4.2382          |


### Framework versions

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