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x_rotated
aravind-selvam/x_rotated
x_rotated is a image-text-to-text model from aravind-selvam. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Image-Text-to-Text
- Library
- transformers
- License
- mit
- Model type
- vision-encoder-decoder
- Access
- Public
- Created
- May 23, 2023
- Updated
- May 23, 2023
- SHA
- 2a618973
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Datasets
Model card
From the Hugging Face model README
<!-- 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. -->
x_rotated
This model is a fine-tuned version of naver-clova-ix/donut-base on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.1574
- Cer: 0.0377
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: 8
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.2067 | 1.0 | 500 | 0.2103 | 0.0538 |
| 0.1043 | 2.0 | 1000 | 0.1667 | 0.0445 |
| 0.0667 | 3.0 | 1500 | 0.1571 | 0.0388 |
| 0.0489 | 4.0 | 2000 | 0.1574 | 0.0377 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
- Task
- Image-Text-to-Text
- Library
- transformers
- Type
- vision-encoder-decoder
- License
- mit
- Created
- May 23, 2023
- Updated
- May 23, 2023