--- library_name: transformers tags: - generated_from_trainer datasets: - wikitext metrics: - accuracy model-index: - name: gpt2-verification results: - task: name: Causal Language Modeling type: text-generation dataset: name: wikitext wikitext-2-raw-v1 type: wikitext args: wikitext-2-raw-v1 metrics: - name: Accuracy type: accuracy value: 0.18546350602802217 --- # gpt2-verification This model utilizes the GPT2 architecture and GPT2 tokenizer, and was trained from scratch using wikitext-2-raw-v1. It achieves the following results on the evaluation set: - Loss: 6.0571 - Accuracy: 0.1855 ## Model Train Command ``` CUDA_VISIBLE_DEVICES=0 uv run python examples/pytorch/language-modeling/run_clm.py \ --model_type gpt2 \ --tokenizer_name gpt2 \ --dataset_name wikitext \ --dataset_config_name wikitext-2-raw-v1 \ --per_device_train_batch_size 2 \ --per_device_eval_batch_size 2 \ --num_train_epochs 3 \ --do_train \ --do_eval \ --output_dir ./output/gpt2-test \ --save_steps 500 \ --logging_steps 100 \ --push_to_hub \ --hub_model_id "yasutoshi-lab/gpt2-verification" --hub_private_repo true \ --hub_strategy "end" ``` ## 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: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - 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: linear - num_epochs: 3.0 ### Training results ### Framework versions - Transformers 5.6.0.dev0 - Pytorch 2.11.0+cu128 - Datasets 4.8.4 - Tokenizers 0.22.2