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x_rotatedv2 – AI Model by aravind-selvam | AlphaNeural AI
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x_rotatedv2
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transformers
pytorch
tensorboard
vision-encoder-decoder
image-to-text
generated_from_trainer
imagefolder
mit
endpoints_compatible
us
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x_rotatedv2
This model is a fine-tuned version of
naver-clova-ix/donut-base
on the imagefolder dataset. It achieves the following results on the evaluation set:
Loss: 0.1377
Cer: 0.0410
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: 2e-05
train_batch_size: 8
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
num_epochs: 4
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Cer
0.1068
1.0
1000
0.1668
0.0419
0.0613
2.0
2000
0.1441
0.0428
0.0418
3.0
3000
0.1364
0.0387
0.0285
4.0
4000
0.1377
0.0410
Framework versions
Transformers 4.27.4
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3
