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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_ver6d_coco_swin_gpt2_50Bpc_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_ver6d_coco_swin_gpt2_50Bpc_1e
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+
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+ This model is a fine-tuned version of [VK246/IC_ver6c_coco_swin_gpt2_50Apc_1e](https://huggingface.co/VK246/IC_ver6c_coco_swin_gpt2_50Apc_1e) on the coco dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7897
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+ - Rouge1: 42.1846
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+ - Rouge2: 16.6343
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+ - Rougel: 38.2927
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+ - Rougelsum: 38.2913
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+ - Bleu: 10.4949
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+ - Gen Len: 11.3063
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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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+ | 0.7741 | 0.17 | 500 | 0.8245 | 40.8216 | 15.539 | 37.1564 | 37.1436 | 9.6536 | 11.3063 |
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+ | 0.7813 | 0.34 | 1000 | 0.8155 | 41.2707 | 15.9841 | 37.4357 | 37.4254 | 10.033 | 11.3063 |
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+ | 0.782 | 0.51 | 1500 | 0.8061 | 41.6066 | 16.0222 | 37.802 | 37.8009 | 9.9619 | 11.3063 |
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+ | 0.79 | 0.68 | 2000 | 0.7985 | 41.6881 | 16.2489 | 37.9303 | 37.9178 | 10.3074 | 11.3063 |
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+ | 0.7888 | 0.85 | 2500 | 0.7929 | 42.1145 | 16.5388 | 38.2401 | 38.2324 | 10.3546 | 11.3063 |
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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