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checkpoints – AI Model by Quinametzin | AlphaNeural AI
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checkpoints
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transformers
safetensors
layoutlmv3
token-classification
generated_from_trainer
microsoft/layoutlmv3-base
finetune
cc-by-nc-sa-4.0
autotrain_compatible
endpoints_compatible
us
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checkpoints
This model is a fine-tuned version of
microsoft/layoutlmv3-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0489
Precision: 0.8842
Recall: 0.9068
F1: 0.8953
Accuracy: 0.9849
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: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
No log
1.2658
100
0.0575
0.8673
0.8744
0.8708
0.9815
No log
2.5316
200
0.0490
0.8876
0.8970
0.8923
0.9846
Framework versions
Transformers 4.45.1
Pytorch 2.4.0
Datasets 3.0.1
Tokenizers 0.20.0
