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medsiglip-448-vindr-lora – AI Model by aysangh | AlphaNeural AI
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aysangh
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medsiglip-448-vindr-lora
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peft
tensorboard
safetensors
adapter
lora
transformers
google/medsiglip-448
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medsiglip-448-vindr-lora
This model is a fine-tuned version of
google/medsiglip-448
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.9237
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: 3e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 64
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: 5
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
2.524
0.4938
100
1.3698
0.9851
0.9877
200
0.9441
0.9155
1.4790
300
0.9346
0.8986
1.9728
400
0.9283
0.8851
2.4642
500
0.9243
0.8963
2.9580
600
0.9237
Framework versions
PEFT 0.17.0
Transformers 4.55.0
Pytorch 2.8.0+cu128
Datasets 4.0.0
Tokenizers 0.21.4
