Qwen2.5-7B-Instruct-Resume-LoRA – AI Model by Ella0506 | AlphaNeural AI

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Ella0506/
Qwen2.5-7B-Instruct-Resume-LoRA

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Qwen/Qwen2.5-7B-Instruct

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This model is a fine-tuned version of Qwen/Qwen2.5-7B-Instruct on the resume_qwen2 dataset. It achieves the following results on the evaluation set:

Loss: 0.3422

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: 8e-05
train_batch_size: 1
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 2
total_train_batch_size: 16
total_eval_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 4
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
0.3835	1.4815	1000	0.3827
0.3345	2.9630	2000	0.3457

Framework versions

PEFT 0.12.0
Transformers 4.44.2
Pytorch 2.2.0
Datasets 2.21.0
Tokenizers 0.19.1