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TomSchut/
phi-3-mini-LoRA

generated_from_trainer

microsoft/Phi-3-mini-4k-instruct

adapter

mit

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phi-3-mini-LoRA

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: 0.3153

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
gradient_accumulation_steps: 4
total_train_batch_size: 32
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
2.564	0.1763	100	0.5477
0.3761	0.3526	200	0.3389
0.3323	0.5289	300	0.3310
0.3286	0.7052	400	0.3266
0.3229	0.8814	500	0.3234
0.3229	1.0577	600	0.3213
0.3201	1.2340	700	0.3211
0.3165	1.4103	800	0.3212
0.3189	1.5866	900	0.3189
0.3181	1.7629	1000	0.3185
0.3166	1.9392	1100	0.3180
0.3152	2.1155	1200	0.3172
0.3153	2.2918	1300	0.3169
0.3148	2.4680	1400	0.3168
0.3131	2.6443	1500	0.3158
0.3139	2.8206	1600	0.3155
0.3134	2.9969	1700	0.3153

Framework versions

PEFT 0.12.0
Transformers 4.44.0
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.19.1

TomSchut/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

TomSchut/
phi-3-mini-LoRA