metadata
base_model: microsoft/Phi-3.5-mini-instruct
library_name: peft
license: mit
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: phi-3-mini-LoRA
results: []
phi-3-mini-LoRA
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: 0.4630
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: 1e-05
- 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: 0.2
- training_steps: 250
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.6578 | 1.3333 | 5 | 1.6863 |
| 1.6277 | 2.6667 | 10 | 1.6771 |
| 1.615 | 4.0 | 15 | 1.6615 |
| 1.5879 | 5.3333 | 20 | 1.6372 |
| 1.5835 | 6.6667 | 25 | 1.6028 |
| 1.5908 | 8.0 | 30 | 1.5586 |
| 1.5143 | 9.3333 | 35 | 1.5012 |
| 1.4633 | 10.6667 | 40 | 1.4352 |
| 1.3414 | 12.0 | 45 | 1.3606 |
| 1.3229 | 13.3333 | 50 | 1.2811 |
| 1.2218 | 14.6667 | 55 | 1.2119 |
| 1.1352 | 16.0 | 60 | 1.1488 |
| 1.0852 | 17.3333 | 65 | 1.0885 |
| 0.9989 | 18.6667 | 70 | 1.0299 |
| 0.9959 | 20.0 | 75 | 0.9757 |
| 0.921 | 21.3333 | 80 | 0.9205 |
| 0.8727 | 22.6667 | 85 | 0.8683 |
| 0.8067 | 24.0 | 90 | 0.8200 |
| 0.7785 | 25.3333 | 95 | 0.7783 |
| 0.7139 | 26.6667 | 100 | 0.7396 |
| 0.7081 | 28.0 | 105 | 0.7095 |
| 0.6705 | 29.3333 | 110 | 0.6824 |
| 0.6177 | 30.6667 | 115 | 0.6613 |
| 0.6106 | 32.0 | 120 | 0.6418 |
| 0.575 | 33.3333 | 125 | 0.6239 |
| 0.5904 | 34.6667 | 130 | 0.6083 |
| 0.5917 | 36.0 | 135 | 0.5927 |
| 0.5051 | 37.3333 | 140 | 0.5801 |
| 0.5169 | 38.6667 | 145 | 0.5656 |
| 0.5442 | 40.0 | 150 | 0.5542 |
| 0.5112 | 41.3333 | 155 | 0.5432 |
| 0.5061 | 42.6667 | 160 | 0.5321 |
| 0.5071 | 44.0 | 165 | 0.5234 |
| 0.4373 | 45.3333 | 170 | 0.5119 |
| 0.4476 | 46.6667 | 175 | 0.5049 |
| 0.3914 | 48.0 | 180 | 0.4972 |
| 0.465 | 49.3333 | 185 | 0.4914 |
| 0.4122 | 50.6667 | 190 | 0.4890 |
| 0.4209 | 52.0 | 195 | 0.4837 |
| 0.3933 | 53.3333 | 200 | 0.4784 |
| 0.3583 | 54.6667 | 205 | 0.4760 |
| 0.3952 | 56.0 | 210 | 0.4727 |
| 0.3858 | 57.3333 | 215 | 0.4708 |
| 0.3433 | 58.6667 | 220 | 0.4707 |
| 0.4041 | 60.0 | 225 | 0.4680 |
| 0.3558 | 61.3333 | 230 | 0.4665 |
| 0.382 | 62.6667 | 235 | 0.4650 |
| 0.3625 | 64.0 | 240 | 0.4638 |
| 0.3513 | 65.3333 | 245 | 0.4644 |
| 0.3541 | 66.6667 | 250 | 0.4630 |
Framework versions
- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0