gpt2-larger-luther

<!-- 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. -->

22_12_13_luther_blocks_larger_fp16_20ep

This model is a fine-tuned version of stefan-it/german-gpt2-larger on a dataset of texts by Martin Luther. It achieves the following results on the evaluation set:

• Loss: 3.5847
• Accuracy: 0.3168

Model description

This is a language model used to generate wishes for a happy new year to the readers of "reformiert" a journal in Switzerland (https://www.reformiert.info)

Intended uses & limitations

This is to test the capabilities of the GPT-2 transformer architecture.

Training and evaluation data

Automatic split of an edited and "cleaned" version of parts of Luther's writing. Cleaning refers here to the process of eliminating para-texts like page numbering, footnotes, etc.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 20.0
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.26.0.dev0
• Pytorch 1.13.0
• Datasets 2.7.1
• Tokenizers 0.12.1