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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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<!-- 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_ver6c_coco_swin_gpt2_50Apc_1e |
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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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## 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 | 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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### Framework versions |
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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 |
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