phi3.5-mini-adapter_v1

This model is a fine-tuned version of microsoft/Phi-3.5-mini-instruct on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0998

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: 3e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.05
• num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss
14.2062	0.6061	10	13.2015
5.0286	1.2121	20	3.9207
0.248	1.8182	30	0.2396
0.1801	2.4242	40	0.1860
0.1496	3.0303	50	0.1639
0.212	3.6364	60	0.1333
0.0822	4.2424	70	0.1134
0.07	4.8485	80	0.1061
0.0871	5.4545	90	0.1178
0.0645	6.0606	100	0.1017
0.0558	6.6667	110	0.0998

Framework versions

• PEFT 0.11.1
• Transformers 4.43.1
• Pytorch 2.4.0+cu121
• Datasets 2.19.1
• Tokenizers 0.19.1