Downloads · 30 days
9
20% of all-time downloads
donut_experiment_bayesian_trial_9
davelotito/donut_experiment_bayesian_trial_9
donut_experiment_bayesian_trial_9 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. --
All-time downloads
46
Public
Parameters
202M
1.6 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors809 MB · 99%
Parameter types
How the weights are stored.
F32202M · 100%
Try a prompt
Base models
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_9
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: 0.5922
- Bleu: 0.0587
- Precisions: [0.735655737704918, 0.6310904872389791, 0.5668449197860963, 0.5173501577287066]
- Brevity Penalty: 0.0967
- Length Ratio: 0.2998
- Translation Length: 488
- Reference Length: 1628
- Cer: 0.7688
- Wer: 0.8559
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: 1.393489197537874e-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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1.1982 | 1.0 | 253 | 0.7300 | 0.0555 | [0.6828282828282828, 0.5616438356164384, 0.5091863517060368, 0.45987654320987653] | 0.1014 | 0.3041 | 495 | 1628 | 0.7812 | 0.8659 |
| 0.5755 | 2.0 | 506 | 0.5922 | 0.0587 | [0.735655737704918, 0.6310904872389791, 0.5668449197860963, 0.5173501577287066] | 0.0967 | 0.2998 | 488 | 1628 | 0.7688 | 0.8559 |
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