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donut_experiment_bayesian_trial_1
davelotito/donut_experiment_bayesian_trial_1
donut_experiment_bayesian_trial_1 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_1
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: 0.4856
- Bleu: 0.0696
- Precisions: [0.8274428274428275, 0.7712264150943396, 0.7356948228882834, 0.6935483870967742]
- Brevity Penalty: 0.0921
- Length Ratio: 0.2955
- Translation Length: 481
- Reference Length: 1628
- Cer: 0.7518
- Wer: 0.8247
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: 7.862160042303398e-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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.0892 | 1.0 | 253 | 0.5425 | 0.0656 | [0.8221757322175732, 0.7505938242280285, 0.7005494505494505, 0.6482084690553745] | 0.0902 | 0.2936 | 478 | 1628 | 0.7544 | 0.8316 |
| 0.0402 | 2.0 | 506 | 0.4856 | 0.0696 | [0.8274428274428275, 0.7712264150943396, 0.7356948228882834, 0.6935483870967742] | 0.0921 | 0.2955 | 481 | 1628 | 0.7518 | 0.8247 |
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
- May 20, 2024
- Updated
- May 20, 2024