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qwen3-8b-mmlu_prox-lora-sw – AI Model by xummer | AlphaNeural AI
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qwen3-8b-mmlu_prox-lora-sw
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This model is a fine-tuned version of
Qwen/Qwen3-8B
on the mmlu_prox_sw_train dataset. It achieves the following results on the evaluation set:
Loss: 0.3600
Accuracy: 0.8692
Mcq Accuracy: 0.3464
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: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
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: 0.1
num_epochs: 3.0
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
Mcq Accuracy
0.3130
2.5367
200
0.3602
0.8690
0.3458
Framework versions
PEFT 0.18.1
Transformers 5.2.0
Pytorch 2.10.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2
