| | --- |
| | license: apache-2.0 |
| | base_model: dandelin/vilt-b32-finetuned-vqa |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: ViLT_FT_Balanced_Binary_Abstract_Scenes |
| | 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. --> |
| |
|
| | # ViLT_FT_Balanced_Binary_Abstract_Scenes |
| | |
| | This model is a fine-tuned version of [dandelin/vilt-b32-finetuned-vqa](https://huggingface.co/dandelin/vilt-b32-finetuned-vqa) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.3521 |
| | |
| | ## 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: 0.0005 |
| | - train_batch_size: 8 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 3 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:-----:|:----:|:---------------:| |
| | | 1.6688 | 0.17 | 200 | 1.6769 | |
| | | 1.3841 | 0.34 | 400 | 1.6145 | |
| | | 1.3773 | 0.5 | 600 | 1.5574 | |
| | | 1.3539 | 0.67 | 800 | 1.5374 | |
| | | 1.3458 | 0.84 | 1000 | 1.5044 | |
| | | 1.3653 | 1.01 | 1200 | 1.4956 | |
| | | 1.3222 | 1.18 | 1400 | 1.4968 | |
| | | 1.3362 | 1.34 | 1600 | 1.4855 | |
| | | 1.3557 | 1.51 | 1800 | 1.3809 | |
| | | 1.3207 | 1.68 | 2000 | 1.3806 | |
| | | 1.348 | 1.85 | 2200 | 1.3718 | |
| | | 1.3215 | 2.02 | 2400 | 1.3677 | |
| | | 1.3299 | 2.18 | 2600 | 1.3793 | |
| | | 1.335 | 2.35 | 2800 | 1.3662 | |
| | | 1.3033 | 2.52 | 3000 | 1.3628 | |
| | | 1.3377 | 2.69 | 3200 | 1.3525 | |
| | | 1.3001 | 2.85 | 3400 | 1.3521 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.37.2 |
| | - Pytorch 2.1.0+cu121 |
| | - Datasets 2.17.0 |
| | - Tokenizers 0.15.2 |
| | |
