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LLaVA-trained-paper – AI Model by Aranya31 | AlphaNeural AI
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Aranya31
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LLaVA-trained-paper
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peft
tensorboard
safetensors
generated_from_trainer
llava-hf/llava-1.5-7b-hf
adapter
llama2
us
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LLaVA-trained-paper
This model is a fine-tuned version of
llava-hf/llava-1.5-7b-hf
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.4388
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: 0.0002
train_batch_size: 1
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 2
optimizer: Use adamw_hf 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
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
0.0307
1.0
861
0.4172
0.0206
2.0
1722
0.4240
0.0105
3.0
2583
0.4388
Framework versions
PEFT 0.14.0
Transformers 4.49.0.dev0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0
