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qwen3-8b-nli-lora-de – AI Model by xummer | AlphaNeural AI
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qwen3-8b-nli-lora-de
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llama-factory
lora
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Qwen/Qwen3-8B
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This model is a fine-tuned version of
Qwen/Qwen3-8B
on the nli_de_train dataset. It achieves the following results on the evaluation set:
Loss: 0.1702
Accuracy: 0.9481
Mcq Accuracy: 0.7896
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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
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
0.0839
1.5984
500
0.1362
0.9418
0.784
Framework versions
PEFT 0.18.1
Transformers 5.2.0
Pytorch 2.10.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2
