phi-2_summarize – AI Model by deboramachadoandrade | AlphaNeural AI

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deboramachadoandrade/
phi-2_summarize

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microsoft/phi-2

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phi-2_summarize

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

Loss: 1.7266

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: 0.0005
train_batch_size: 1
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 3
training_steps: 400

Training results

Training Loss	Epoch	Step	Validation Loss
1.9986	0.03	25	1.8320
1.8726	0.06	50	1.7854
1.7545	0.08	75	1.7727
1.8384	0.11	100	1.7614
1.7279	0.14	125	1.7561
1.7348	0.17	150	1.7503
1.8037	0.2	175	1.7442
1.7602	0.23	200	1.7418
1.8112	0.25	225	1.7372
1.7011	0.28	250	1.7339
1.6925	0.31	275	1.7312
1.6696	0.34	300	1.7295
1.7461	0.37	325	1.7275
1.6521	0.4	350	1.7270
1.6636	0.42	375	1.7267
1.7048	0.45	400	1.7266

Framework versions

PEFT 0.10.0
Transformers 4.39.3
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2