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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: 0.3303

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
0.9579	0.3367	100	0.4585
0.4008	0.6734	200	0.3733
0.363	1.0101	300	0.3535
0.3461	1.3468	400	0.3450
0.3371	1.6835	500	0.3378
0.3327	2.0202	600	0.3339
0.3275	2.3569	700	0.3317
0.3274	2.6936	800	0.3303

Framework versions

PEFT 0.11.1
Transformers 4.43.1
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1

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