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-QLoRA
results: []
phi-3-mini-QLoRA
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: 0.5741
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- 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 |
|---|---|---|---|
| 1.1422 | 0.1810 | 100 | 0.6625 |
| 0.6238 | 0.3619 | 200 | 0.6002 |
| 0.5932 | 0.5429 | 300 | 0.5906 |
| 0.5926 | 0.7238 | 400 | 0.5860 |
| 0.5794 | 0.9048 | 500 | 0.5834 |
| 0.5868 | 1.0857 | 600 | 0.5815 |
| 0.5711 | 1.2667 | 700 | 0.5796 |
| 0.5729 | 1.4476 | 800 | 0.5785 |
| 0.5858 | 1.6286 | 900 | 0.5772 |
| 0.5732 | 1.8095 | 1000 | 0.5763 |
| 0.5736 | 1.9905 | 1100 | 0.5756 |
| 0.5638 | 2.1715 | 1200 | 0.5754 |
| 0.5769 | 2.3524 | 1300 | 0.5746 |
| 0.5668 | 2.5334 | 1400 | 0.5745 |
| 0.5675 | 2.7143 | 1500 | 0.5742 |
| 0.5693 | 2.8953 | 1600 | 0.5741 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1