--- base_model: VK246/IC_ver6e_coco_swin_gpt2_50Apc_1e tags: - generated_from_trainer datasets: - coco metrics: - rouge model-index: - name: IC_ver6F_coco_swin_gpt2_50B_1e results: [] --- # IC_ver6F_coco_swin_gpt2_50B_1e This model is a fine-tuned version of [VK246/IC_ver6e_coco_swin_gpt2_50Apc_1e](https://huggingface.co/VK246/IC_ver6e_coco_swin_gpt2_50Apc_1e) on the coco dataset. It achieves the following results on the evaluation set: - Loss: 0.7799 - Cider: 5.8986 - Rouge1: 42.1787 - Rouge2: 16.6289 - Rougel: 38.245 - Rougelsum: 38.236 - Bleu-1: 43.2152 - Bleu-2: 25.0563 - Bleu-3: 15.845 - Bleu-4: 10.5042 - Gen Len: 11.3063 ## 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: 96 - eval_batch_size: 96 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 1 ### Training results | Training Loss | Epoch | Step | Validation Loss | Cider | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu-1 | Bleu-2 | Bleu-3 | Bleu-4 | Gen Len | |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|:-------:|:-------:|:-------:| | 0.6972 | 0.34 | 1000 | 0.8128 | 5.8314 | 41.3992 | 16.1278 | 37.5675 | 37.5537 | 42.6637 | 24.5815 | 15.5018 | 10.2465 | 11.3063 | | 0.7318 | 0.68 | 2000 | 0.7912 | 6.9716 | 41.8244 | 16.3282 | 37.9594 | 37.9525 | 42.7623 | 24.7305 | 15.6458 | 10.4067 | 11.3063 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.4 - Tokenizers 0.13.3