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pkbiswas/
Phi-3.5-Mini-Instruct-Summarization-QLoRa

Name: Phi-3.5-Mini-Instruct-Summarization-QLoRa
Availability: InStock

peft

tensorboard

safetensors

generated_from_trainer

summarization

scitldr

microsoft/Phi-3.5-mini-instruct

adapter

mit

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Phi-3.5-Mini-Instruct-Summarization-QLoRa

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

Loss: 2.1376

Model description

More information needed

Intended uses & limitations

Summarization

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 0.0002
train_batch_size: 1
eval_batch_size: 1
seed: 42
optimizer: Use paged_adamw_32bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 2
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
2.0519	0.2510	500	2.1280
2.0279	0.5020	1000	2.1223
2.0514	0.7530	1500	2.1131
2.0313	1.0040	2000	2.1142
1.8923	1.2550	2500	2.1390
1.8487	1.5060	3000	2.1375
1.819	1.7570	3500	2.1376

Framework versions

PEFT 0.14.0
Transformers 4.47.1
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

pkbiswas/Phi-3.5-Mini-Instruct-Summarization-QLoRa