transformers tensorboard safetensors gpt2 text-generation generated_from_trainer en dataset:Elriggs/openwebtext-100k autotrain_compatible endpoints_compatible text-generation-inference region:us
---
tags:
- generated_from_trainer
model-index:
- name: 100Kopenwebtextgptlite_OpenWebText100K
  results: []
datasets:
- Elriggs/openwebtext-100k
language:
- en
pipeline_tag: text-generation
---

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# 100Kopenwebtextgptlite_OpenWebText100K

This model has trained on [this](https://huggingface.co/datasets/Elriggs/openwebtext-100k) dataset
It achieves the following results on the evaluation set:
- Loss: 5.3490

## Model description

The model use GPT 2 Architecture

## Intended uses & limitations

The limitation of this model is that the loss is still quite high, so this model is not suitable for text use. 

## Training and evaluation data

You can check [this](https://wandb.ai/111202113467/huggingface/runs/55wdfxkx/workspace?workspace=user-111202113467) graph for training and eval loss

## Training procedure

- Dataset: `openwebtext100k`

- Training Hardware: 2x T4 GPU from Kaggle

- Download dataset -> setup hyperparams -> training

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 7.2717        | 0.36  | 1000  | 6.6089          |
| 6.4412        | 0.71  | 2000  | 6.2425          |
| 6.1733        | 1.07  | 3000  | 6.0212          |
| 5.9827        | 1.42  | 4000  | 5.8614          |
| 5.8549        | 1.78  | 5000  | 5.7380          |
| 5.7444        | 2.13  | 6000  | 5.6440          |
| 5.6548        | 2.49  | 7000  | 5.5686          |
| 5.5952        | 2.84  | 8000  | 5.5093          |
| 5.5363        | 3.2   | 9000  | 5.4604          |
| 5.4867        | 3.55  | 10000 | 5.4216          |
| 5.4578        | 3.91  | 11000 | 5.3911          |
| 5.4288        | 4.27  | 12000 | 5.3697          |
| 5.4082        | 4.62  | 13000 | 5.3555          |
| 5.4009        | 4.98  | 14000 | 5.3490          |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.17.1
- Tokenizers 0.15.1