ca-finetuned-phi-2 – AI Model by lvcalucioli | AlphaNeural AI

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lvcalucioli/
ca-finetuned-phi-2

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microsoft/phi-2

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ca-finetuned-phi-2

This model is a fine-tuned version of microsoft/phi-2 on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.5643
Perplexity: 0.0000

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: 0.001
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 32
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.05
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Perplexity
No log	0.97	7	2.2352	0.0000
No log	1.95	14	2.0164	0.0000
2.4567	2.92	21	1.8511	0.0000
2.4567	3.9	28	1.7391	0.0000
1.8517	4.87	35	1.6667	0.0000
1.8517	5.98	43	1.6059	0.0000
1.5627	6.96	50	1.5816	0.0000
1.5627	7.93	57	1.5672	0.0000
1.41	8.9	64	1.5650	0.0000
1.41	9.74	70	1.5643	0.0000

Framework versions

PEFT 0.8.2
Transformers 4.38.0.dev0
Pytorch 2.0.1+cu117
Datasets 2.16.1
Tokenizers 0.15.1