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SFT-Qwen3-30B-dsetV3 – AI Model by tam2003 | AlphaNeural AI
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tam2003
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SFT-Qwen3-30B-dsetV3
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peft
safetensors
adapter
lora
transformers
text-generation
conversational
Qwen/Qwen3-Coder-30B-A3B-Instruct
apache-2.0
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SFT-Qwen3-30B-dsetV3
This model is a fine-tuned version of
Qwen/Qwen3-Coder-30B-A3B-Instruct
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.6872
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: 5
eval_batch_size: 5
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 10
optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.03
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
0.7767
0.625
30
0.7523
0.568
1.25
60
0.7073
0.5549
1.875
90
0.6872
0.3923
2.5
120
0.6952
0.4057
3.125
150
0.7339
0.213
3.75
180
0.7525
Framework versions
PEFT 0.18.0
Transformers 4.57.1
Pytorch 2.8.0+cu126
Datasets 4.4.1
Tokenizers 0.22.1
