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unicodec-fisher – AI Model by voidful | AlphaNeural AI
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voidful
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unicodec-fisher
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peft
safetensors
adapter
lora
transformers
text-generation
conversational
Qwen/Qwen3-4B-Instruct-2507
apache-2.0
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unicodec-fisher
This model is a fine-tuned version of
Qwen/Qwen3-4B-Instruct-2507
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 11.8818
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: 42
gradient_accumulation_steps: 8
total_train_batch_size: 8
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: 1
Training results
Training Loss
Epoch
Step
Validation Loss
11.8744
1.0
21597
11.8818
Framework versions
PEFT 0.18.0
Transformers 4.57.3
Pytorch 2.9.0.dev20250629+cu128
Datasets 2.21.0
Tokenizers 0.22.1
