donut_experiment_bayesian_trial_5 – AI Model by davelotito | AlphaNeural AI

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davelotito/
donut_experiment_bayesian_trial_5

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vision-encoder-decoder

generated_from_trainer

naver-clova-ix/donut-base

endpoints_compatible

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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