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LightOnOCR-2-1B-pl-pdf – AI Model by aquaqamelob | AlphaNeural AI
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LightOnOCR-2-1B-pl-pdf
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peft
adapter
lora
transformers
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lightonai/LightOnOCR-2-1B
apache-2.0
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LightOnOCR-2-ft-polish_pdf
This model is a fine-tuned version of
lightonai/LightOnOCR-2-1B
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0080
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: 4e-05
train_batch_size: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 0.05
training_steps: 250
Training results
Training Loss
Epoch
Step
Validation Loss
0.0301
0.3137
50
0.0162
0.0069
0.6275
100
0.0090
0.0108
0.9412
150
0.0083
0.0070
1.2510
200
0.0081
0.0145
1.5647
250
0.0080
Framework versions
PEFT 0.19.1
Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 4.8.5
Tokenizers 0.22.2
