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scoring_qwen3-1.7B – AI Model by fisher422 | AlphaNeural AI
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fisher422
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scoring_qwen3-1.7B
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transformers
safetensors
qwen3
text-generation
llama-factory
full
generated_from_trainer
conversational
other
autotrain_compatible
text-generation-inference
endpoints_compatible
us
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Model card
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test7000
本模型基于Qwen3－1.7B，通过指令微调，模型可以对满足输入格式的文本进行数据打分，打分涉及4个维度。 This model is a fine-tuned version of
Qwen3-1.7B
on the test7000 dataset.
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: 2e-05
train_batch_size: 2
eval_batch_size: 8
seed: 43
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 4
total_train_batch_size: 64
total_eval_batch_size: 64
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
num_epochs: 1.0
Training results
Framework versions
Transformers 4.51.3
Pytorch 2.7.1+cu126
Datasets 3.5.0
Tokenizers 0.21.1
