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florence2_output – AI Model by mmrech | AlphaNeural AI
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mmrech
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florence2_output
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peft
safetensors
adapter
lora
transformers
text-generation
microsoft/Florence-2-base
mit
us
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florence2_output
This model is a fine-tuned version of
microsoft/Florence-2-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 1.5346
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: 0.0001
train_batch_size: 4
eval_batch_size: 4
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: 50
training_steps: 500
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
1.7452
25.0
100
1.7258
1.1957
50.0
200
1.4125
1.1343
75.0
300
1.4571
1.0557
100.0
400
1.5572
1.0336
125.0
500
1.5346
Framework versions
PEFT 0.18.1
Transformers 4.57.3
Pytorch 2.9.1+cu128
Datasets 4.4.2
Tokenizers 0.22.2
