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2and3_apps_30k_v6-SFT-Qwen3-8B – AI Model by huseyinatahaninan | AlphaNeural AI
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2and3_apps_30k_v6-SFT-Qwen3-8B
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transformers
safetensors
qwen3
text-generation
llama-factory
full
generated_from_trainer
conversational
Qwen/Qwen3-8B
finetune
apache-2.0
autotrain_compatible
text-generation-inference
endpoints_compatible
us
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2and3_apps_30k_v6-SFT-Qwen3-8B
This model is a fine-tuned version of
Qwen/Qwen3-8B
on the 2and3_apps_30k_v6 dataset. It achieves the following results on the evaluation set:
Loss: 0.1796
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: 5e-06
train_batch_size: 1
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 4
total_train_batch_size: 32
total_eval_batch_size: 8
optimizer: Use 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: 1.0
Training results
Training Loss
Epoch
Step
Validation Loss
0.1861
0.3478
100
0.1875
0.1827
0.6957
200
0.1807
Framework versions
Transformers 4.52.4
Pytorch 2.8.0+cu128
Datasets 3.6.0
Tokenizers 0.21.1
