File size: 2,243 Bytes
3b49764 |
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 |
---
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: []
---
<!-- 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. -->
# phi-3-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: 0.5741
## 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 |