metadata
tags:
- generated_from_trainer
datasets:
- coco
metrics:
- rouge
- bleu
model-index:
- name: vit-swin-base-224-gpt2-image-captioning
results: []
vit-swin-base-224-gpt2-image-captioning
This model is a fine-tuned version of on the coco dataset. It achieves the following results on the evaluation set:
- Loss: 1.0848
- Rouge1: 29.903
- Rouge2: 7.441
- Rougel: 28.0811
- Rougelsum: 28.1133
- Bleu: 3.2506
- Gen Len: 11.116
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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Training results
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1