metadata
license: mit
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: microsoft/Phi-3-mini-4k-instruct
model-index:
- name: phi-3-mini-LoRA
results: []
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: 0.5601
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 |
|---|---|---|---|
| 1.1716 | 0.1809 | 100 | 0.6639 |
| 0.6253 | 0.3618 | 200 | 0.5865 |
| 0.5772 | 0.5427 | 300 | 0.5753 |
| 0.5823 | 0.7237 | 400 | 0.5703 |
| 0.5862 | 0.9046 | 500 | 0.5673 |
| 0.5804 | 1.0855 | 600 | 0.5652 |
| 0.5776 | 1.2664 | 700 | 0.5641 |
| 0.5721 | 1.4473 | 800 | 0.5630 |
| 0.5725 | 1.6282 | 900 | 0.5623 |
| 0.5708 | 1.8091 | 1000 | 0.5615 |
| 0.5714 | 1.9900 | 1100 | 0.5611 |
| 0.5685 | 2.1710 | 1200 | 0.5607 |
| 0.5618 | 2.3519 | 1300 | 0.5605 |
| 0.5789 | 2.5328 | 1400 | 0.5605 |
| 0.5716 | 2.7137 | 1500 | 0.5600 |
| 0.5626 | 2.8946 | 1600 | 0.5601 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1