--- base_model: VK246/IC_ver6M_coco_swin_gpt2_50A_1e tags: - generated_from_trainer datasets: - coco metrics: - rouge model-index: - name: IC_ver6N_coco_swin_gpt2_50B_1e results: [] --- # IC_ver6N_coco_swin_gpt2_50B_1e This model is a fine-tuned version of [VK246/IC_ver6M_coco_swin_gpt2_50A_1e](https://huggingface.co/VK246/IC_ver6M_coco_swin_gpt2_50A_1e) on the coco dataset. It achieves the following results on the evaluation set: - Loss: 0.8687 - Cider: 72.5295 - Rouge1: 41.1356 - Rouge2: 15.6403 - Rougel: 37.2276 - Rougelsum: 37.2406 - Bleu-1: 42.1796 - Bleu-2: 24.0186 - Bleu-3: 14.9974 - Bleu-4: 9.8206 - 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 | |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|:-------:|:------:|:-------:| | 0.3812 | 0.34 | 1000 | 1.0009 | 68.2568 | 39.9649 | 14.5975 | 36.1435 | 36.1441 | 41.3234 | 23.0865 | 14.2103 | 9.2075 | 11.3063 | | 0.5147 | 0.68 | 2000 | 0.8687 | 72.5295 | 41.1356 | 15.6403 | 37.2276 | 37.2406 | 42.1796 | 24.0186 | 14.9974 | 9.8206 | 11.3063 | ### Framework versions - Transformers 4.32.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.4 - Tokenizers 0.13.3