|
--- |
|
base_model: microsoft/dit-base-finetuned-rvlcdip |
|
tags: |
|
- image-classification |
|
- vision |
|
- generated_from_trainer |
|
metrics: |
|
- f1 |
|
model-index: |
|
- name: donut-base-beans |
|
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. --> |
|
|
|
# donut-base-beans |
|
|
|
This model is a fine-tuned version of [microsoft/dit-base-finetuned-rvlcdip](https://huggingface.co/microsoft/dit-base-finetuned-rvlcdip) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0404 |
|
- F1: 0.6134 |
|
|
|
## 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: 3e-05 |
|
- train_batch_size: 64 |
|
- eval_batch_size: 64 |
|
- seed: 1337 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- training_steps: 10000 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | F1 | Validation Loss | |
|
|:-------------:|:------:|:----:|:------:|:---------------:| |
|
| 0.1165 | 0.0126 | 50 | 0.4177 | 0.0642 | |
|
| 0.0942 | 0.0252 | 100 | 0.4772 | 0.0485 | |
|
| 0.1076 | 0.0379 | 150 | 0.4643 | 0.0584 | |
|
| 0.1103 | 0.0505 | 200 | nan | 0.0446 | |
|
| 0.0873 | 0.0631 | 250 | 0.5313 | 0.0518 | |
|
| 0.1053 | 0.0757 | 300 | 0.5329 | 0.0736 | |
|
| 0.0797 | 0.0884 | 350 | 0.5326 | 0.0726 | |
|
| 0.0857 | 0.1010 | 400 | 0.5498 | 0.0693 | |
|
| 0.0885 | 0.1136 | 450 | nan | 0.0917 | |
|
| 0.102 | 0.1262 | 500 | 0.5649 | 0.0580 | |
|
| 0.0716 | 0.1389 | 550 | 0.5381 | 0.0797 | |
|
| 0.0854 | 0.1515 | 600 | 0.5718 | 0.0744 | |
|
| 0.089 | 0.1641 | 650 | 0.5790 | 0.0504 | |
|
| 0.0721 | 0.1767 | 700 | 0.5727 | 0.0618 | |
|
| 0.0721 | 0.1893 | 750 | 0.5904 | 0.0703 | |
|
| 0.0865 | 0.2020 | 800 | 0.5953 | 0.0588 | |
|
| 0.0767 | 0.2146 | 850 | 0.5918 | 0.0437 | |
|
| 0.0773 | 0.2272 | 900 | 0.5957 | 0.0568 | |
|
| 0.0748 | 0.2398 | 950 | 0.5942 | 0.0465 | |
|
| 0.0761 | 0.2525 | 1000 | nan | 0.0660 | |
|
| 0.0855 | 0.2651 | 1050 | 0.5964 | 0.0491 | |
|
| 0.0832 | 0.2777 | 1100 | 0.6048 | 0.0498 | |
|
| 0.0821 | 0.2903 | 1150 | 0.6032 | 0.0597 | |
|
| 0.0715 | 0.3030 | 1200 | nan | 0.0643 | |
|
| 0.085 | 0.3156 | 1250 | 0.6054 | 0.0659 | |
|
| 0.0826 | 0.3282 | 1300 | 0.6012 | 0.0556 | |
|
| 0.064 | 0.3408 | 1350 | nan | 0.0564 | |
|
| 0.0854 | 0.3534 | 1400 | nan | 0.0552 | |
|
| 0.0702 | 0.3661 | 1450 | 0.6061 | 0.0675 | |
|
| 0.0771 | 0.3787 | 1500 | nan | 0.0578 | |
|
| 0.08 | 0.3913 | 1550 | nan | 0.0492 | |
|
| 0.0804 | 0.4039 | 1600 | 0.6112 | 0.0538 | |
|
| 0.083 | 0.4166 | 1650 | 0.6048 | 0.0579 | |
|
| 0.0701 | 0.4292 | 1700 | 0.6045 | 0.0674 | |
|
| 0.0721 | 0.4418 | 1750 | 0.5979 | 0.0491 | |
|
| 0.0765 | 0.4544 | 1800 | nan | 0.0439 | |
|
| 0.0692 | 0.4671 | 1850 | 0.6058 | 0.0468 | |
|
| 0.0761 | 0.4797 | 1900 | 0.6125 | 0.0574 | |
|
| 0.0757 | 0.4923 | 1950 | 0.6126 | 0.0569 | |
|
| 0.0654 | 0.5049 | 2000 | 0.6095 | 0.0549 | |
|
| 0.0736 | 0.5175 | 2050 | 0.0538 | 0.6122 | |
|
| 0.0685 | 0.5302 | 2100 | 0.0485 | 0.6104 | |
|
| 0.0726 | 0.5428 | 2150 | 0.0566 | 0.6120 | |
|
| 0.0731 | 0.5554 | 2200 | 0.0585 | 0.6112 | |
|
| 0.0722 | 0.5680 | 2250 | 0.0589 | 0.6140 | |
|
| 0.0819 | 0.5807 | 2300 | 0.0505 | 0.6122 | |
|
| 0.0694 | 0.5933 | 2350 | 0.0537 | 0.6101 | |
|
| 0.0705 | 0.6059 | 2400 | 0.0646 | 0.6130 | |
|
| 0.0702 | 0.6185 | 2450 | 0.0462 | 0.6124 | |
|
| 0.0709 | 0.6312 | 2500 | 0.0404 | 0.6134 | |
|
| 0.0804 | 0.6438 | 2550 | 0.0478 | 0.6123 | |
|
| 0.0666 | 0.6564 | 2600 | 0.0455 | 0.6104 | |
|
| 0.0749 | 0.6690 | 2650 | 0.0479 | 0.6132 | |
|
| 0.067 | 0.6816 | 2700 | 0.0558 | 0.6132 | |
|
| 0.068 | 0.6943 | 2750 | 0.0539 | 0.6108 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.43.0.dev0 |
|
- Pytorch 2.1.2+cu118 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
|
|
