metadata

base_model: microsoft/Phi-3-mini-4k-instruct
library_name: peft
license: mit
tags:
  - trl
  - sft
  - generated_from_trainer
model-index:
  - name: phi-3-mini-LoRA-MEDQA-Extended-V3
    results: []

phi-3-mini-LoRA-MEDQA-Extended-V3

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: 0.6233

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: 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: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
0.7825	0.0882	200	0.6760
0.6593	0.1764	400	0.6488
0.6454	0.2646	600	0.6424
0.6424	0.3528	800	0.6382
0.6382	0.4410	1000	0.6358
0.6342	0.5292	1200	0.6340
0.6355	0.6174	1400	0.6327
0.6355	0.7055	1600	0.6315
0.6336	0.7937	1800	0.6307
0.6321	0.8819	2000	0.6298
0.6321	0.9701	2200	0.6291
0.6298	1.0583	2400	0.6286
0.6285	1.1465	2600	0.6280
0.628	1.2347	2800	0.6275
0.6282	1.3229	3000	0.6271
0.6278	1.4111	3200	0.6267
0.6257	1.4993	3400	0.6264
0.6276	1.5875	3600	0.6260
0.6253	1.6757	3800	0.6256
0.6253	1.7639	4000	0.6253
0.6242	1.8521	4200	0.6250
0.6252	1.9402	4400	0.6247
0.6239	2.0284	4600	0.6246
0.6222	2.1166	4800	0.6244
0.6226	2.2048	5000	0.6242
0.6219	2.2930	5200	0.6241
0.6227	2.3812	5400	0.6240
0.6195	2.4694	5600	0.6239
0.6219	2.5576	5800	0.6237
0.6221	2.6458	6000	0.6236
0.6238	2.7340	6200	0.6235
0.621	2.8222	6400	0.6234
0.621	2.9104	6600	0.6234
0.6222	2.9986	6800	0.6233

Framework versions

PEFT 0.12.0
Transformers 4.43.3
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1