Beta
Explore
Marketplace
Neural Labs
Chat
Wallet
Docs
lora_finetune – AI Model by prakharsinghal | AlphaNeural AI
You can deploy this model and start earning money today!
prakharsinghal
/
lora_finetune
like
0
peft
safetensors
adapter
lora
transformers
text-generation
conversational
Qwen/Qwen2.5-0.5B-Instruct
apache-2.0
us
Views
No views yet
Model card
Files and Versions
Community
API
Deploy
lora_finetune
This model is a fine-tuned version of
Qwen/Qwen2.5-0.5B-Instruct
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.8675
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: 2e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
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: linear
lr_scheduler_warmup_steps: 100
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
0.8734
0.9988
1000
0.8738
0.8169
1.9968
2000
0.8689
0.8325
2.9948
3000
0.8675
Framework versions
PEFT 0.17.0
Transformers 4.55.0
Pytorch 2.6.0+cu124
Datasets 4.0.0
Tokenizers 0.21.4
