Llama2-7B-lora-r-32-generic-step-200-lr-1e-5-labels_40.0 – AI Model by Siqi-Hu | AlphaNeural AI

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Siqi-Hu/
Llama2-7B-lora-r-32-generic-step-200-lr-1e-5-labels_40.0

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meta-llama/Llama-2-7b-hf

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Llama2-7B-lora-r-32-generic-step-200-lr-1e-5-labels_40.0

This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 3.7152

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: 1e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 20
training_steps: 200
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
5.4728	0.3653	20	5.5435
4.9739	0.7306	40	4.8172
4.2871	1.0959	60	4.3050
4.0458	1.4612	80	4.0568
3.9287	1.8265	100	3.9036
3.7825	2.1918	120	3.8103
3.6987	2.5571	140	3.7566
3.7338	2.9224	160	3.7278
3.6426	3.2877	180	3.7169
3.6798	3.6530	200	3.7152

Framework versions

PEFT 0.15.2
Transformers 4.45.2
Pytorch 2.5.0+cu121
Datasets 3.2.0
Tokenizers 0.20.3