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LightOnOCR-2-1B-Math-Handwritten – AI Model by sprok-daniel-mozaik | AlphaNeural AI
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sprok-daniel-mozaik
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LightOnOCR-2-1B-Math-Handwritten
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peft
safetensors
adapter
lora
transformers
text-generation
conversational
lightonai/LightOnOCR-2-1B
apache-2.0
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LightOnOCR-2-1B-Math-Handwritten
This model is a fine-tuned version of
lightonai/LightOnOCR-2-1B
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.3156
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: 6e-05
train_batch_size: 4
eval_batch_size: 6
seed: 42
gradient_accumulation_steps: 4
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: linear
lr_scheduler_warmup_steps: 10
num_epochs: 1
Training results
Training Loss
Epoch
Step
Validation Loss
1.1458
0.16
50
0.5339
0.4190
0.32
100
0.3892
0.3376
0.48
150
0.3491
0.3011
0.64
200
0.3280
0.2831
0.8
250
0.3190
0.2877
0.96
300
0.3156
Framework versions
PEFT 0.18.1
Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 4.8.4
Tokenizers 0.22.2
