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---
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
should probably proofread and complete it, then remove this comment. -->
# 🧠 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 |