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---
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base_model: VK246/IC_ver6e_coco_swin_gpt2_50Apc_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_ver6F_coco_swin_gpt2_50B_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_ver6F_coco_swin_gpt2_50B_1e
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This model is a fine-tuned version of [VK246/IC_ver6e_coco_swin_gpt2_50Apc_1e](https://huggingface.co/VK246/IC_ver6e_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: 0.7799
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- Cider: 5.8986
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- Rouge1: 42.1787
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- Rouge2: 16.6289
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- Rougel: 38.245
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- Rougelsum: 38.236
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- Bleu-1: 43.2152
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- Bleu-2: 25.0563
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- Bleu-3: 15.845
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- Bleu-4: 10.5042
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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 | Cider | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu-1 | Bleu-2 | Bleu-3 | Bleu-4 | Gen Len |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|:-------:|:-------:|:-------:|
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| 0.6972 | 0.34 | 1000 | 0.8128 | 5.8314 | 41.3992 | 16.1278 | 37.5675 | 37.5537 | 42.6637 | 24.5815 | 15.5018 | 10.2465 | 11.3063 |
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| 0.7318 | 0.68 | 2000 | 0.7912 | 6.9716 | 41.8244 | 16.3282 | 37.9594 | 37.9525 | 42.7623 | 24.7305 | 15.6458 | 10.4067 | 11.3063 |
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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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