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Qwen3-30B-A3B-Base-medqa-seed-2405 – AI Model by airesearch | AlphaNeural AI
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Qwen3-30B-A3B-Base-medqa-seed-2405
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Qwen3-30B-A3B-Base-medqa-seed-2405
This model is a fine-tuned version of
Qwen/Qwen3-30B-A3B-Base
on the medqa dataset. It achieves the following results on the evaluation set:
Loss: 0.0279
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: 2
eval_batch_size: 2
seed: 2405
distributed_type: multi-GPU
num_devices: 128
gradient_accumulation_steps: 8
total_train_batch_size: 2048
total_eval_batch_size: 256
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: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3.0
Training results
Training Loss
Epoch
Step
Validation Loss
2.0528
0.4651
10
1.8944
0.316
0.9302
20
0.1930
0.0322
1.3721
30
0.0318
0.0229
1.8372
40
0.0289
0.0206
2.2791
50
0.0280
0.0238
2.7442
60
0.0280
Framework versions
PEFT 0.15.2
Transformers 4.52.3
Pytorch 2.7.0+cu126
Datasets 3.6.0
Tokenizers 0.21.1
