---
library_name: transformers
license: mit
base_model: HFS26/reuters-gpt2-text-gen
tags:
- generated_from_trainer
model-index:
- name: reuters-gpt2-text-gen
  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. -->

# reuters-gpt2-text-gen

This model is a fine-tuned version of [HFS26/reuters-gpt2-text-gen](https://huggingface.co/HFS26/reuters-gpt2-text-gen) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 4.7212

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 4.5445        | 1.0   | 270  | 4.7212          |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.3
- Tokenizers 0.22.2