GREEN-Phi2 – AI Model by StanfordAIMI | AlphaNeural AI

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StanfordAIMI/
GREEN-Phi2

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text-generation

generated_from_trainer

microsoft/phi-2

autotrain_compatible

text-generation-inference

endpoints_compatible

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Phi-2

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

Loss: 0.0781

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: 0.0001
train_batch_size: 8
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 32
total_train_batch_size: 2048
total_eval_batch_size: 64
optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.05
num_epochs: 12.0

Training results

Training Loss	Epoch	Step	Validation Loss
0.2903	0.64	25	0.1770
0.1566	1.28	50	0.1319
0.1379	1.92	75	0.1253
0.1246	2.56	100	0.1165
0.1159	3.2	125	0.1049
0.1048	3.84	150	0.0998
0.0947	4.48	175	0.0949
0.0872	5.12	200	0.0906
0.0836	5.76	225	0.0890
0.0774	6.39	250	0.0850
0.0717	7.03	275	0.0827
0.0639	7.67	300	0.0807
0.0596	8.31	325	0.0789
0.0555	8.95	350	0.0773
0.0498	9.59	375	0.0777
0.0491	10.23	400	0.0781
0.0467	10.87	425	0.0780
0.0459	11.51	450	0.0781

Framework versions

Transformers 4.38.1
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2