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update model card README.md

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+ ---
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - coco
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+ metrics:
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+ - rouge
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+ - bleu
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+ model-index:
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+ - name: IC_ver6c_coco_swin_gpt2_50Apc_1e
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # IC_ver6c_coco_swin_gpt2_50Apc_1e
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+
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+ This model is a fine-tuned version of [VK246/IC_ver6b_coco_swin_gpt2_50Bpc_1e](https://huggingface.co/VK246/IC_ver6b_coco_swin_gpt2_50Bpc_1e) on the coco dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7946
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+ - Rouge1: 41.9094
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+ - Rouge2: 16.3068
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+ - Rougel: 38.073
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+ - Rougelsum: 38.0746
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+ - Bleu: 10.1966
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+ - Gen Len: 11.2806
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 96
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+ - eval_batch_size: 96
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 1
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu | Gen Len |
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+ |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|
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+ | 0.8232 | 0.17 | 500 | 0.8331 | 40.454 | 15.1311 | 36.7639 | 36.7714 | 9.2957 | 11.2806 |
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+ | 0.8016 | 0.34 | 1000 | 0.8200 | 40.6374 | 15.5346 | 36.902 | 36.9055 | 9.6894 | 11.2806 |
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+ | 0.8048 | 0.51 | 1500 | 0.8136 | 41.3382 | 15.9333 | 37.6502 | 37.6442 | 9.7743 | 11.2806 |
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+ | 0.8018 | 0.68 | 2000 | 0.8028 | 41.5968 | 16.106 | 37.8326 | 37.836 | 9.9815 | 11.2806 |
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+ | 0.8075 | 0.85 | 2500 | 0.7978 | 41.7017 | 16.1589 | 37.8899 | 37.8954 | 10.1244 | 11.2806 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.30.2
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.13.1
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+ - Tokenizers 0.13.3