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donut_experiment_bayesian_trial_14
davelotito/donut_experiment_bayesian_trial_14
donut_experiment_bayesian_trial_14 is a image-text-to-text model from davelotito. 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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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. -->
donut_experiment_bayesian_trial_14
This model is a fine-tuned version of naver-clova-ix/donut-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5314
- Bleu: 0.0658
- Precisions: [0.8375527426160337, 0.7721822541966427, 0.7222222222222222, 0.6798679867986799]
- Brevity Penalty: 0.0876
- Length Ratio: 0.2912
- Translation Length: 474
- Reference Length: 1628
- Cer: 0.7563
- Wer: 0.8271
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: 4.135841372163364e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Precisions | Brevity Penalty | Length Ratio | Translation Length | Reference Length | Cer | Wer |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.0251 | 1.0 | 253 | 0.5332 | 0.0676 | [0.8308977035490606, 0.7677725118483413, 0.7205479452054795, 0.6688311688311688] | 0.0908 | 0.2942 | 479 | 1628 | 0.7498 | 0.8243 |
| 0.0185 | 2.0 | 506 | 0.5314 | 0.0658 | [0.8375527426160337, 0.7721822541966427, 0.7222222222222222, 0.6798679867986799] | 0.0876 | 0.2912 | 474 | 1628 | 0.7563 | 0.8271 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.1.0
- Datasets 2.18.0
- Tokenizers 0.19.1
- Task
- Image-Text-to-Text
- Library
- transformers
- Type
- vision-encoder-decoder
- License
- mit
- Created
- Jun 26, 2024
- Updated
- Jun 26, 2024