phi-2-sft-alpaca_gpt4_en-ep1-lora – AI Model by Yhyu13 | AlphaNeural AI

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Yhyu13/
phi-2-sft-alpaca_gpt4_en-ep1-lora

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microsoft/phi-2

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phi-2-sft-alpaca_gpt4_en-1

This model is a fine-tuned version of microsoft/phi-2 on the alpaca_gpt4_en dataset. It achieves the following results on the evaluation set:

Loss: 0.8625

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: 5e-05
train_batch_size: 1
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 2
gradient_accumulation_steps: 8
total_train_batch_size: 16
total_eval_batch_size: 2
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
num_epochs: 1.0

Training results

Training Loss	Epoch	Step	Validation Loss
1.0325	0.07	200	0.8922
0.9136	0.14	400	0.8801
0.9043	0.21	600	0.8753
0.8903	0.27	800	0.8711
0.9056	0.34	1000	0.8683
0.9001	0.41	1200	0.8673
0.8949	0.48	1400	0.8668
0.8917	0.55	1600	0.8656
0.8951	0.62	1800	0.8648
0.9014	0.68	2000	0.8637
0.8874	0.75	2200	0.8630
0.8968	0.82	2400	0.8628
0.8755	0.89	2600	0.8626
0.9029	0.96	2800	0.8625

Framework versions

PEFT 0.7.1
Transformers 4.36.1
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.15.0