---
license: mit
tags:
- generated_from_trainer
datasets:
- generator
model-index:
- name: gpt2-cl-length-sampling-3
  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-3

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: 5.0773

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 6.5331        | 0.04  | 500   | 5.9440          |
| 5.252         | 0.08  | 1000  | 5.5557          |
| 4.9523        | 0.13  | 1500  | 5.3662          |
| 4.7542        | 0.17  | 2000  | 5.2549          |
| 4.6126        | 0.21  | 2500  | 5.1817          |
| 4.5013        | 0.25  | 3000  | 5.1317          |
| 4.3981        | 0.3   | 3500  | 5.1037          |
| 4.3046        | 0.34  | 4000  | 5.0879          |
| 4.2161        | 0.38  | 4500  | 5.0611          |
| 4.1315        | 0.42  | 5000  | 5.0483          |
| 4.0506        | 0.47  | 5500  | 5.0318          |
| 3.9631        | 0.51  | 6000  | 5.0247          |
| 3.8821        | 0.55  | 6500  | 5.0143          |
| 3.8021        | 0.59  | 7000  | 5.0233          |
| 3.723         | 0.64  | 7500  | 5.0218          |
| 3.6421        | 0.68  | 8000  | 5.0249          |
| 3.5797        | 0.72  | 8500  | 5.0276          |
| 3.513         | 0.76  | 9000  | 5.0309          |
| 3.4736        | 0.8   | 9500  | 5.0316          |
| 3.4299        | 0.85  | 10000 | 5.0367          |
| 3.4015        | 0.89  | 10500 | 5.0340          |
| 3.3834        | 0.93  | 11000 | 5.0330          |
| 3.3717        | 0.97  | 11500 | 5.0333          |


### Framework versions

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