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--- |
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base_model: VK246/IC_ver6d_coco_swin_gpt2_50Bpc_1e |
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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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model-index: |
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- name: IC_ver6e_coco_swin_gpt2_50Apc_1e |
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results: [] |
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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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# IC_ver6e_coco_swin_gpt2_50Apc_1e |
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This model is a fine-tuned version of [VK246/IC_ver6d_coco_swin_gpt2_50Bpc_1e](https://huggingface.co/VK246/IC_ver6d_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: 0.7783 |
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- Cider: 19.1116 |
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- Rouge1: 42.2076 |
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- Rouge2: 16.6791 |
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- Rougel: 38.4352 |
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- Rougelsum: 38.4324 |
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- Bleu-1: 42.9768 |
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- Bleu-2: 25.0535 |
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- Bleu-3: 15.8932 |
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- Bleu-4: 10.5581 |
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- Gen Len: 11.2806 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Cider | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu-1 | Bleu-2 | Bleu-3 | Bleu-4 | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|:-------:|:-------:|:-------:| |
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| 0.7299 | 0.17 | 500 | 0.8169 | 15.1223 | 40.4746 | 15.1013 | 36.817 | 36.8166 | 41.7335 | 23.5713 | 14.621 | 9.566 | 11.2806 | |
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| 0.7243 | 0.34 | 1000 | 0.8063 | 15.7288 | 41.2081 | 15.8926 | 37.4018 | 37.4016 | 42.2656 | 24.2595 | 15.2602 | 10.0788 | 11.2806 | |
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| 0.7396 | 0.51 | 1500 | 0.7999 | 15.5164 | 41.6231 | 16.1665 | 38.0103 | 38.0119 | 42.0958 | 24.3223 | 15.2851 | 10.0869 | 11.2806 | |
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| 0.7507 | 0.68 | 2000 | 0.7879 | 15.3421 | 41.9871 | 16.4909 | 38.2491 | 38.2515 | 42.6606 | 24.7464 | 15.6329 | 10.3731 | 11.2806 | |
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| 0.7712 | 0.85 | 2500 | 0.7820 | 11.751 | 41.9906 | 16.5153 | 38.2624 | 38.2634 | 42.8539 | 24.8663 | 15.7151 | 10.3989 | 11.2806 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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