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my_trocr
minhphat5399/my_trocr
my_trocr is a image-text-to-text model from minhphat5399. 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.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Image-Text-to-Text
- Library
- transformers
- Model type
- vision-encoder-decoder
- Access
- Public
- Created
- Aug 17, 2023
- Updated
- Aug 17, 2023
- SHA
- 64e1c60c
Try a prompt
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. -->
my_trocr
This model is a fine-tuned version of microsoft/trocr-small-printed on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3975
- Cer: 0.0185
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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 | Cer |
|---|---|---|---|---|
| 13.6251 | 1.0 | 82 | 0.5465 | 0.1229 |
| 13.6251 | 2.0 | 164 | 0.4406 | 0.0274 |
| 13.6251 | 3.0 | 246 | 0.3975 | 0.0185 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
- Task
- Image-Text-to-Text
- Library
- transformers
- Type
- vision-encoder-decoder
- Created
- Aug 17, 2023
- Updated
- Aug 17, 2023