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qwen-lora-finetune – AI Model by tumengcho | AlphaNeural AI
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qwen-lora-finetune
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peft
tensorboard
safetensors
adapter
lora
text-generation
conversational
deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
mit
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qwen-lora-finetune
This model is a fine-tuned version of
deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 1.0582
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: 1
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 8
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
1.2116
0.4164
500
1.2138
1.1185
0.8329
1000
1.1236
1.1033
1.2490
1500
1.0895
1.0628
1.6655
2000
1.0743
1.0511
2.0816
2500
1.0653
1.0631
2.4981
3000
1.0601
1.0501
2.9145
3500
1.0582
Framework versions
PEFT 0.17.1
Transformers 4.57.1
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1
