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donut_experiment_bayesian_trial_5
davelotito/donut_experiment_bayesian_trial_5
donut_experiment_bayesian_trial_5 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_5
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: 0.4541
- Bleu: 0.0661
- Precisions: [0.8029045643153527, 0.731764705882353, 0.6875, 0.639871382636656]
- Brevity Penalty: 0.0928
- Length Ratio: 0.2961
- Translation Length: 482
- Reference Length: 1628
- Cer: 0.7590
- Wer: 0.8315
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: 0.00018010138886762352
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.655 | 1.0 | 253 | 0.5770 | 0.0681 | [0.7555110220440882, 0.6719457013574661, 0.625974025974026, 0.5762195121951219] | 0.1041 | 0.3065 | 499 | 1628 | 0.7627 | 0.8438 |
| 0.183 | 2.0 | 506 | 0.4541 | 0.0661 | [0.8029045643153527, 0.731764705882353, 0.6875, 0.639871382636656] | 0.0928 | 0.2961 | 482 | 1628 | 0.7590 | 0.8315 |
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 30, 2024
- Updated
- May 30, 2024