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Qwen30b-sft-no-feedback – AI Model by formalmathatepfl | AlphaNeural AI
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Qwen30b-sft-no-feedback
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transformers
safetensors
qwen3_moe
text-generation
llama-factory
full
generated_from_trainer
conversational
Qwen/Qwen3-30B-A3B
finetune
other
endpoints_compatible
us
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sft-no-feedback
This model is a fine-tuned version of
Qwen/Qwen3-30B-A3B
on the sft dataset. It achieves the following results on the evaluation set:
Loss: 0.0638
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: 8e-06
train_batch_size: 1
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 8
total_train_batch_size: 8
total_eval_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: cosine
lr_scheduler_warmup_steps: 0.03
num_epochs: 2.0
Training results
Training Loss
Epoch
Step
Validation Loss
0.0721
0.3529
3000
0.0748
0.0646
0.7058
6000
0.0684
0.0585
1.0587
9000
0.0657
0.0520
1.4116
12000
0.0646
0.0576
1.7645
15000
0.0640
Framework versions
Transformers 5.2.0
Pytorch 2.11.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2
