Bitamin_mutimodal
This model is a fine-tuned version of ddobokki/vision-encoder-decoder-vit-gpt2-coco-ko on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0644
- Rouge1: 6.6906
- Rouge2: 3.2986
- Rougel: 6.6499
- Rougelsum: 6.6803
- 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 |
|---|---|---|---|---|---|---|---|---|
| 0.2001 | 1.0 | 2982 | 0.1589 | 0.0 | 0.0 | 0.0 | 0.0 | 100.0 |
| 0.1178 | 2.0 | 5964 | 0.1095 | 0.8554 | 0.7275 | 0.8315 | 0.8554 | 100.0 |
| 0.0778 | 3.0 | 8946 | 0.0829 | 2.7168 | 1.6458 | 2.7157 | 2.6864 | 100.0 |
| 0.0552 | 4.0 | 11928 | 0.0691 | 5.454 | 2.6068 | 5.4184 | 5.4101 | 100.0 |
| 0.0396 | 5.0 | 14910 | 0.0644 | 6.6906 | 3.2986 | 6.6499 | 6.6803 | 100.0 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
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