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eda-llm-qwen2.5-lora – AI Model by beAnalytic | AlphaNeural AI
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beAnalytic
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eda-llm-qwen2.5-lora
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peft
tensorboard
safetensors
adapter
lora
transformers
text-generation
conversational
Qwen/Qwen2.5-1.5B-Instruct
apache-2.0
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eda-llm-qwen2.5-lora
This model is a fine-tuned version of
Qwen/Qwen2.5-1.5B-Instruct
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 1.6368
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: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 8
optimizer: Use adamw_torch_fused 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: 200
num_epochs: 3.0
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
1.6840
3.0
93
1.6368
Framework versions
PEFT 0.18.1
Transformers 5.4.0
Pytorch 2.11.0+cu130
Datasets 4.3.0
Tokenizers 0.22.1
