--- license: apache-2.0 tags: - generated_from_trainer metrics: - rouge - bleu model-index: - name: vit results: [] --- # vit This model is a fine-tuned version of [nlpconnect/vit-gpt2-image-captioning](https://huggingface.co/nlpconnect/vit-gpt2-image-captioning) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.2973 - Rouge1: 67.9673 - Rouge2: 58.9518 - Rougel: 67.1789 - Rougelsum: 67.324 - Bleu: 54.4707 - Gen Len: 7.7647 ## 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: 4 - eval_batch_size: 4 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 4 ### Training results ### Framework versions - Transformers 4.28.0 - Pytorch 2.0.0+cu118 - Datasets 2.11.0 - Tokenizers 0.13.3