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Qwen3-8B-Chess-SFT – AI Model by ljcnju | AlphaNeural AI | AlphaNeural AI
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ljcnju
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Qwen3-8B-Chess-SFT
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transformers
safetensors
qwen3
text-generation
llama-factory
full
generated_from_trainer
conversational
2509.24239
other
text-generation-inference
endpoints_compatible
us
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Model description
This model is the SFT stage two model of paper
https://arxiv.org/abs/2509.24239
.
Training and evaluation data
Training dataset:
https://huggingface.co/datasets/ljcnju/ChessArena_Training_Dataset
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 5e-06
train_batch_size: 1
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 4
total_train_batch_size: 32
total_eval_batch_size: 8
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: 0.1
num_epochs: 3.0
Training results
Training Loss
Epoch
Step
Validation Loss
0.5441
0.5667
500
0.5742
0.462
1.1326
1000
0.5241
0.4573
1.6993
1500
0.4992
0.4061
2.2652
2000
0.4926
0.3979
2.8320
2500
0.4887
Framework versions
Transformers 4.52.4
Pytorch 2.8.0+cu128
Datasets 3.6.0
Tokenizers 0.21.1
