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--- |
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license: apache-2.0 |
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base_model: nlpconnect/vit-gpt2-image-captioning |
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tags: |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: image-captioning-output |
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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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# image-captioning-output |
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This model is a fine-tuned version of [nlpconnect/vit-gpt2-image-captioning](https://huggingface.co/nlpconnect/vit-gpt2-image-captioning) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5164 |
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- Rouge1: 35.5267 |
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- Rouge2: 12.254 |
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- Rougel: 32.968 |
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- Rougelsum: 32.9723 |
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- Gen Len: 12.395 |
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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: 4 |
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- eval_batch_size: 4 |
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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: 3.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
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| 0.5193 | 0.25 | 500 | 0.5171 | 33.0319 | 10.364 | 30.6939 | 30.6888 | 12.1 | |
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| 0.4842 | 0.5 | 1000 | 0.5102 | 33.7318 | 10.8199 | 31.1842 | 31.18 | 11.3 | |
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| 0.4724 | 0.75 | 1500 | 0.5028 | 34.6981 | 11.4074 | 31.9128 | 31.9158 | 12.02 | |
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| 0.4632 | 1.0 | 2000 | 0.5012 | 35.9443 | 12.8742 | 33.4061 | 33.377 | 11.04 | |
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| 0.377 | 1.25 | 2500 | 0.5026 | 35.7745 | 12.2309 | 33.3234 | 33.3353 | 11.735 | |
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| 0.3819 | 1.5 | 3000 | 0.5018 | 36.0145 | 13.0296 | 33.5985 | 33.6182 | 12.285 | |
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| 0.3788 | 1.75 | 3500 | 0.5030 | 35.9016 | 12.5276 | 33.4995 | 33.5033 | 11.305 | |
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| 0.3654 | 2.0 | 4000 | 0.5020 | 36.2476 | 12.945 | 33.6453 | 33.6595 | 11.9 | |
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| 0.3102 | 2.25 | 4500 | 0.5146 | 36.1507 | 13.0072 | 33.3889 | 33.3786 | 12.305 | |
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| 0.3137 | 2.5 | 5000 | 0.5166 | 35.7413 | 12.5693 | 33.2646 | 33.2508 | 12.71 | |
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| 0.3111 | 2.75 | 5500 | 0.5171 | 35.5658 | 12.511 | 33.0581 | 33.0518 | 12.55 | |
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| 0.3023 | 3.0 | 6000 | 0.5164 | 35.5267 | 12.254 | 32.968 | 32.9723 | 12.395 | |
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### Framework versions |
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- Transformers 4.40.0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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