| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - f1 |
| | base_model: google/vit-base-patch16-224-in21k |
| | model-index: |
| | - name: iiif_manuscript_vit |
| | 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. --> |
| |
|
| | # iiif_manuscript_vit |
| |
|
| | 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 None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.5684 |
| | - F1: 0.5996 |
| |
|
| | ## 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: 2e-05 |
| | - train_batch_size: 64 |
| | - eval_batch_size: 64 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 10 |
| | - mixed_precision_training: Native AMP |
| | - label_smoothing_factor: 0.1 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | F1 | |
| | |:-------------:|:-----:|:-----:|:---------------:|:------:| |
| | | 0.5639 | 1.0 | 2269 | 0.5822 | 0.5516 | |
| | | 0.5834 | 2.0 | 4538 | 0.5825 | 0.5346 | |
| | | 0.5778 | 3.0 | 6807 | 0.5794 | 0.6034 | |
| | | 0.5735 | 4.0 | 9076 | 0.5742 | 0.5713 | |
| | | 0.5731 | 5.0 | 11345 | 0.5745 | 0.6008 | |
| | | 0.5701 | 6.0 | 13614 | 0.5729 | 0.5499 | |
| | | 0.5696 | 7.0 | 15883 | 0.5717 | 0.5952 | |
| | | 0.5683 | 8.0 | 18152 | 0.5680 | 0.6005 | |
| | | 0.5648 | 9.0 | 20421 | 0.5679 | 0.5967 | |
| | | 0.564 | 10.0 | 22690 | 0.5684 | 0.5996 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.16.2 |
| | - Pytorch 1.10.0+cu111 |
| | - Datasets 1.18.3 |
| | - Tokenizers 0.11.0 |
| |
|
