File size: 2,234 Bytes
8535e7a |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 |
---
base_model: microsoft/Phi-3-mini-4k-instruct
library_name: peft
license: mit
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: phi3-mini-QLoRA
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# phi3-mini-QLoRA
This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5590
## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.9007 | 0.1810 | 100 | 0.6361 |
| 0.606 | 0.3619 | 200 | 0.5831 |
| 0.5789 | 0.5429 | 300 | 0.5755 |
| 0.5797 | 0.7238 | 400 | 0.5709 |
| 0.5653 | 0.9048 | 500 | 0.5687 |
| 0.573 | 1.0857 | 600 | 0.5663 |
| 0.5577 | 1.2667 | 700 | 0.5648 |
| 0.5586 | 1.4476 | 800 | 0.5636 |
| 0.572 | 1.6286 | 900 | 0.5623 |
| 0.5594 | 1.8095 | 1000 | 0.5616 |
| 0.5585 | 1.9905 | 1100 | 0.5614 |
| 0.5486 | 2.1715 | 1200 | 0.5609 |
| 0.5614 | 2.3524 | 1300 | 0.5599 |
| 0.5515 | 2.5334 | 1400 | 0.5597 |
| 0.5525 | 2.7143 | 1500 | 0.5593 |
| 0.5545 | 2.8953 | 1600 | 0.5590 |
### Framework versions
- PEFT 0.13.0
- Transformers 4.45.1
- Pytorch 2.2.2
- Datasets 3.0.1
- Tokenizers 0.20.0 |