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qwen_chess_lora – AI Model by parom23 | AlphaNeural AI
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parom23
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qwen_chess_lora
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transformers
safetensors
qwen2
text-generation
generated_from_trainer
conversational
Qwen/Qwen2.5-0.5B-Instruct
finetune
apache-2.0
text-generation-inference
endpoints_compatible
us
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qwen_chess_lora
This model is a fine-tuned version of
Qwen/Qwen2.5-0.5B-Instruct
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.2985
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: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
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: linear
num_epochs: 1
mixed_precision_training: Native AMP
Training results
Framework versions
Transformers 5.2.0
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.2
