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Qwen3.5-0.8B-legal_extraction-BASELINE – AI Model by kamizane | AlphaNeural AI
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kamizane
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Qwen3.5-0.8B-legal_extraction-BASELINE
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peft
safetensors
adapter
lora
transformers
text-generation
conversational
Qwen/Qwen3.5-0.8B
apache-2.0
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Qwen3.5-0.8B-legal_extraction-BASELINE
This model is a fine-tuned version of
Qwen/Qwen3.5-0.8B
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.0601
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: 0.0001
train_batch_size: 1
eval_batch_size: 1
seed: 14
gradient_accumulation_steps: 6
total_train_batch_size: 6
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: linear
num_epochs: 4
Training results
Training Loss
Epoch
Step
Validation Loss
0.0562
2.5350
200
0.0555
0.0562
4.0
316
0.0601
Framework versions
PEFT 0.20.0
Transformers 5.15.1
Pytorch 2.11.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2
