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Qwen3.5-9B-eSFT – AI Model by zhengbang0707 | AlphaNeural AI
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Qwen3.5-9B-eSFT
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transformers
safetensors
qwen3_5
image-text-to-text
llama-factory
full
generated_from_trainer
conversational
Qwen/Qwen3.5-9B
finetune
other
endpoints_compatible
us
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Qwen3.5-9B-full-eSFT
This model is a fine-tuned version of
Qwen/Qwen3.5-9B
on the vlguard_Qwen3.5-9B_eSFT dataset. It achieves the following results on the evaluation set:
Loss: 1.1175
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: 1e-05
train_batch_size: 1
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 2
gradient_accumulation_steps: 128
total_train_batch_size: 256
total_eval_batch_size: 2
optimizer: Use OptimizerNames.ADAMW_TORCH 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: 0.03
num_epochs: 3.0
Training results
Training Loss
Epoch
Step
Validation Loss
0.8568
3.0
24
1.1175
Framework versions
Transformers 5.6.0
Pytorch 2.5.1+cu121
Datasets 4.0.0
Tokenizers 0.22.2
