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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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<!-- 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_ver6d_coco_swin_gpt2_50Bpc_1e |
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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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## 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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| 0.7741 | 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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### 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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