---
license: mit
base_model: gpt2
tags:
- generated_from_trainer
model-index:
- name: GPT2-124M-wikitext-v0.1
  results: []
datasets:
- wikitext
pipeline_tag: text-generation
co2_eq_emissions:
  emissions: 500
  training_type: "fine-tuning"
  source: "mlco2"
  geographical_location: "Bucharest, Romania"
  hardware_used: "1 x RTX 4090 GPU"
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# 🧠 GPT2-124M-wikitext-v0.1

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the [wikitext](https://huggingface.co/datasets/wikitext).
It achieves the following results on the evaluation set:
- Loss: 2.9841

## Model description

This is a practical hands-on experience for better understanding 🤗 Transformers and 🤗 Datasets. This model is GPT2(124M) fine-tuned on wikitext(103-raw-v1) on 1 x RTX 4090.

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step   | Validation Loss |
|:-------------:|:-----:|:------:|:---------------:|
| 3.1335        | 1.0   | 57467  | 3.0363          |
| 3.0643        | 2.0   | 114934 | 2.9968          |
| 3.0384        | 3.0   | 172401 | 2.9841          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0