---
license: mit
tags:
- generated_from_trainer
datasets:
- generator
model-index:
- name: gpt2-cl-length-sampling
  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-cl-length-sampling

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: 5.0276

## 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: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 6.4896        | 0.1   | 500  | 5.9335          |
| 5.1803        | 0.2   | 1000 | 5.5576          |
| 4.871         | 0.3   | 1500 | 5.3672          |
| 4.6547        | 0.4   | 2000 | 5.2453          |
| 4.5086        | 0.5   | 2500 | 5.1611          |
| 4.3642        | 0.6   | 3000 | 5.0948          |
| 4.2412        | 0.7   | 3500 | 5.0350          |
| 4.1326        | 0.8   | 4000 | 4.9978          |
| 4.0612        | 0.9   | 4500 | 4.9717          |
| 4.0255        | 1.0   | 5000 | 4.9665          |


### Framework versions

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