satyakada-iv/phi-3-mini-LoRA-de

phi-3-mini-LoRA

This model is a fine-tuned version of microsoft/Phi-3-mini-128k-instruct on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.2692

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
1.7153	0.1766	100	1.4475
1.429	0.3532	200	1.4079
1.3977	0.5298	300	1.3931
1.3835	0.7064	400	1.3778
1.3612	0.8830	500	1.3640
1.3483	1.0596	600	1.3483
1.3115	1.2362	700	1.3340
1.2945	1.4128	800	1.3180
1.2829	1.5894	900	1.3074
1.2691	1.7660	1000	1.2954
1.26	1.9426	1100	1.2865
1.2259	2.1192	1200	1.2805
1.2117	2.2958	1300	1.2761
1.2001	2.4724	1400	1.2722
1.2035	2.6490	1500	1.2697
1.1836	2.8256	1600	1.2692

Framework versions

• PEFT 0.11.1
• Transformers 4.41.2
• Pytorch 2.3.0+cu121
• Datasets 2.19.1
• Tokenizers 0.19.1