---
license: mit
tags:
- generated_from_trainer
datasets:
- generator
model-index:
- name: gpt2-concat-second
  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-second

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: 4.4031

## 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 6.7063        | 0.29  | 500   | 5.6161          |
| 5.3409        | 0.58  | 1000  | 5.1879          |
| 4.9975        | 0.87  | 1500  | 4.9292          |
| 4.7248        | 1.16  | 2000  | 4.7819          |
| 4.5625        | 1.45  | 2500  | 4.6577          |
| 4.4518        | 1.74  | 3000  | 4.5536          |
| 4.3506        | 2.02  | 3500  | 4.4718          |
| 4.1444        | 2.31  | 4000  | 4.4324          |
| 4.1299        | 2.6   | 4500  | 4.3859          |
| 4.097         | 2.89  | 5000  | 4.3383          |
| 3.9322        | 3.18  | 5500  | 4.3372          |
| 3.8738        | 3.47  | 6000  | 4.3092          |
| 3.8743        | 3.76  | 6500  | 4.2795          |
| 3.8147        | 4.05  | 7000  | 4.2758          |
| 3.6152        | 4.34  | 7500  | 4.2857          |
| 3.6479        | 4.63  | 8000  | 4.2632          |
| 3.654         | 4.92  | 8500  | 4.2380          |
| 3.4411        | 5.21  | 9000  | 4.2846          |
| 3.398         | 5.49  | 9500  | 4.2785          |
| 3.4249        | 5.78  | 10000 | 4.2628          |
| 3.3498        | 6.07  | 10500 | 4.2910          |
| 3.1525        | 6.36  | 11000 | 4.3119          |
| 3.1727        | 6.65  | 11500 | 4.3057          |
| 3.1862        | 6.94  | 12000 | 4.2985          |
| 2.9723        | 7.23  | 12500 | 4.3475          |
| 2.9448        | 7.52  | 13000 | 4.3551          |
| 2.9617        | 7.81  | 13500 | 4.3526          |
| 2.8946        | 8.1   | 14000 | 4.3748          |
| 2.7783        | 8.39  | 14500 | 4.3866          |
| 2.7819        | 8.68  | 15000 | 4.3904          |
| 2.7913        | 8.96  | 15500 | 4.3905          |
| 2.7052        | 9.25  | 16000 | 4.4009          |
| 2.6969        | 9.54  | 16500 | 4.4029          |
| 2.7           | 9.83  | 17000 | 4.4031          |


### Framework versions

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