This model is a fine-tuned version of microsoft/Phi-3-mini-4k-instruct on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.2057

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: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
1.6123	0.2807	100	1.3855
1.3959	0.5614	200	1.3212
1.2889	0.8421	300	1.2876
1.332	1.1228	400	1.2582
1.2596	1.4035	500	1.2443
1.2424	1.6842	600	1.2284
1.1912	1.9649	700	1.2161
1.1686	2.2456	800	1.2123
1.2223	2.5263	900	1.2074
1.1395	2.8070	1000	1.2057

Framework versions

PEFT 0.12.0
Transformers 4.42.4
Pytorch 2.3.1+cu121
Datasets 2.21.0
Tokenizers 0.19.1

zhangdah/phi-3-mini-LoRA

phi-3-mini-LoRA

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

zhangdah/
phi-3-mini-LoRA