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-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: 0.5761
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: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.1336 | 0.1809 | 100 | 0.6788 |
| 0.6283 | 0.3618 | 200 | 0.6030 |
| 0.5944 | 0.5427 | 300 | 0.5931 |
| 0.5953 | 0.7237 | 400 | 0.5879 |
| 0.5793 | 0.9046 | 500 | 0.5852 |
| 0.5908 | 1.0855 | 600 | 0.5832 |
| 0.5717 | 1.2664 | 700 | 0.5812 |
| 0.5748 | 1.4473 | 800 | 0.5802 |
| 0.5876 | 1.6282 | 900 | 0.5787 |
| 0.5725 | 1.8091 | 1000 | 0.5778 |
| 0.5749 | 1.9900 | 1100 | 0.5772 |
| 0.5646 | 2.1710 | 1200 | 0.5769 |
| 0.5806 | 2.3519 | 1300 | 0.5764 |
| 0.5679 | 2.5328 | 1400 | 0.5762 |
| 0.5683 | 2.7137 | 1500 | 0.5761 |
| 0.5715 | 2.8946 | 1600 | 0.5761 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.1.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1