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--- |
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license: apache-2.0 |
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tags: |
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- image-captioning |
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- generated_from_trainer |
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model-index: |
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- name: ViTGPT2I2A |
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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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# ViTGPT2I2A |
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the vizwiz dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0708 |
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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: 2e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- total_train_batch_size: 4 |
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- total_eval_batch_size: 4 |
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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: 5.0 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| 0.1528 | 0.17 | 1000 | 0.0869 | |
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| 0.0899 | 0.34 | 2000 | 0.0817 | |
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| 0.084 | 0.51 | 3000 | 0.0790 | |
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| 0.0814 | 0.68 | 4000 | 0.0773 | |
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| 0.0803 | 0.85 | 5000 | 0.0757 | |
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| 0.077 | 1.02 | 6000 | 0.0745 | |
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| 0.0739 | 1.19 | 7000 | 0.0740 | |
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| 0.0719 | 1.37 | 8000 | 0.0737 | |
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| 0.0717 | 1.54 | 9000 | 0.0730 | |
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| 0.0731 | 1.71 | 10000 | 0.0727 | |
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| 0.0708 | 1.88 | 11000 | 0.0720 | |
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| 0.0697 | 2.05 | 12000 | 0.0717 | |
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| 0.0655 | 2.22 | 13000 | 0.0719 | |
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| 0.0653 | 2.39 | 14000 | 0.0719 | |
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| 0.0657 | 2.56 | 15000 | 0.0712 | |
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| 0.0663 | 2.73 | 16000 | 0.0710 | |
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| 0.0654 | 2.9 | 17000 | 0.0708 | |
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| 0.0645 | 3.07 | 18000 | 0.0716 | |
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| 0.0616 | 3.24 | 19000 | 0.0712 | |
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| 0.0607 | 3.41 | 20000 | 0.0712 | |
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| 0.0611 | 3.58 | 21000 | 0.0711 | |
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| 0.0615 | 3.76 | 22000 | 0.0711 | |
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| 0.0614 | 3.93 | 23000 | 0.0710 | |
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| 0.0594 | 4.1 | 24000 | 0.0716 | |
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| 0.0587 | 4.27 | 25000 | 0.0715 | |
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| 0.0574 | 4.44 | 26000 | 0.0715 | |
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| 0.0579 | 4.61 | 27000 | 0.0715 | |
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| 0.0581 | 4.78 | 28000 | 0.0715 | |
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| 0.0579 | 4.95 | 29000 | 0.0715 | |
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### Framework versions |
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- Transformers 4.16.2 |
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- Pytorch 1.10.2+cu113 |
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- Datasets 1.18.3 |
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- Tokenizers 0.11.0 |
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