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qwen1.5b-autorag-sft-p1-d0-apec – AI Model by Justin-ChenZhen | AlphaNeural AI
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Justin-ChenZhen
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qwen1.5b-autorag-sft-p1-d0-apec
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peft
safetensors
llama-factory
lora
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Qwen/Qwen2.5-1.5B-Instruct
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qwen1.5b-autorag-sft-p1-d0-apec
This model is a fine-tuned version of
/home/cz/ragen/models/Qwen/Qwen2.5-1.5B-Instruct
on the ragen_qa dataset. It achieves the following results on the evaluation set:
Loss: 0.5150
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: 2
eval_batch_size: 4
seed: 42
distributed_type: multi-GPU
num_devices: 5
gradient_accumulation_steps: 16
total_train_batch_size: 160
total_eval_batch_size: 20
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_ratio: 0.15
num_epochs: 4.0
Training results
Training Loss
Epoch
Step
Validation Loss
0.5345
2.0
20
0.5264
0.5124
4.0
40
0.5150
Framework versions
PEFT 0.15.2
Transformers 4.52.1
Pytorch 2.8.0+cu128
Datasets 3.6.0
Tokenizers 0.21.4
