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rag-llm-qwen2.5-7b-lora-24DEC – AI Model by ngocnamk3er | AlphaNeural AI
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ngocnamk3er
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rag-llm-qwen2.5-7b-lora-24DEC
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peft
safetensors
trl
sft
generated_from_trainer
Qwen/Qwen2.5-7B-Instruct
adapter
apache-2.0
us
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rag-llm-qwen2.5-7b-lora-24DEC
This model is a fine-tuned version of
Qwen/Qwen2.5-7B-Instruct
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.1689
Em: 0.0
F1: 0.9422
Rougel: 0.9497
Refusal Accuracy: 1.0
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: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Em
F1
Rougel
Refusal Accuracy
0.1441
1.0
1128
0.1601
0.0
0.9403
0.9484
1.0
0.1175
2.0
2256
0.1577
0.0
0.9426
0.9501
1.0
0.0949
3.0
3384
0.1689
0.0
0.9422
0.9497
1.0
Framework versions
PEFT 0.10.0
Transformers 4.41.2
Pytorch 2.9.1+cu128
Datasets 2.18.0
Tokenizers 0.19.1
