| | --- |
| | base_model: ddobokki/vision-encoder-decoder-vit-gpt2-coco-ko |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - rouge |
| | model-index: |
| | - name: multimodla-Bitamin |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # multimodla-Bitamin |
| |
|
| | This model is a fine-tuned version of [ddobokki/vision-encoder-decoder-vit-gpt2-coco-ko](https://huggingface.co/ddobokki/vision-encoder-decoder-vit-gpt2-coco-ko) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0055 |
| | - Rouge1: 11.8323 |
| | - Rouge2: 6.4292 |
| | - Rougel: 11.8967 |
| | - Rougelsum: 11.883 |
| | - Gen Len: 100.0 |
| |
|
| | ## Model description |
| |
|
| | More information needed |
| |
|
| | ## Intended uses & limitations |
| |
|
| | More information needed |
| |
|
| | ## Training and evaluation data |
| |
|
| | More information needed |
| |
|
| | ## Training procedure |
| |
|
| | ### Training hyperparameters |
| |
|
| | The following hyperparameters were used during training: |
| | - learning_rate: 5e-05 |
| | - train_batch_size: 4 |
| | - eval_batch_size: 4 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 5 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
| | |:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:| |
| | | 0.1504 | 1.0 | 2982 | 0.1027 | 0.2262 | 0.2262 | 0.2262 | 0.2262 | 100.0 | |
| | | 0.0664 | 2.0 | 5964 | 0.0457 | 1.7181 | 1.2785 | 1.7523 | 1.7256 | 100.0 | |
| | | 0.0281 | 3.0 | 8946 | 0.0185 | 5.3843 | 3.3178 | 5.4006 | 5.4032 | 100.0 | |
| | | 0.0131 | 4.0 | 11928 | 0.0081 | 10.8352 | 5.9986 | 10.7776 | 10.8786 | 100.0 | |
| | | 0.007 | 5.0 | 14910 | 0.0055 | 11.8323 | 6.4292 | 11.8967 | 11.883 | 100.0 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.42.3 |
| | - Pytorch 2.1.2 |
| | - Datasets 2.20.0 |
| | - Tokenizers 0.19.1 |
| |
|
