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---
license: mit
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: microsoft/Phi-3-medium-128k-instruct
model-index:
- name: results
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. -->
# results
This model is a fine-tuned version of [microsoft/Phi-3-medium-128k-instruct](https://huggingface.co/microsoft/Phi-3-medium-128k-instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3259
## 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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.102 | 0.1065 | 100 | 2.1266 |
| 2.0156 | 0.2130 | 200 | 1.9941 |
| 1.8151 | 0.3195 | 300 | 1.8149 |
| 1.6951 | 0.4260 | 400 | 1.5771 |
| 1.2789 | 0.5325 | 500 | 1.3936 |
| 1.0007 | 0.6390 | 600 | 1.1524 |
| 0.7882 | 0.7455 | 700 | 0.9936 |
| 0.9486 | 0.8520 | 800 | 0.8539 |
| 0.7381 | 0.9585 | 900 | 0.7410 |
| 0.6254 | 1.0650 | 1000 | 0.6283 |
| 0.4915 | 1.1715 | 1100 | 0.5834 |
| 0.3432 | 1.2780 | 1200 | 0.5034 |
| 0.349 | 1.3845 | 1300 | 0.4476 |
| 0.4378 | 1.4909 | 1400 | 0.4160 |
| 0.4522 | 1.5974 | 1500 | 0.4061 |
| 0.3183 | 1.7039 | 1600 | 0.3795 |
| 0.3184 | 1.8104 | 1700 | 0.3707 |
| 0.267 | 1.9169 | 1800 | 0.3601 |
| 0.2966 | 2.0234 | 1900 | 0.3538 |
| 0.2697 | 2.1299 | 2000 | 0.3492 |
| 0.3662 | 2.2364 | 2100 | 0.3424 |
| 0.3135 | 2.3429 | 2200 | 0.3407 |
| 0.3339 | 2.4494 | 2300 | 0.3366 |
| 0.1828 | 2.5559 | 2400 | 0.3340 |
| 0.2824 | 2.6624 | 2500 | 0.3306 |
| 0.3204 | 2.7689 | 2600 | 0.3289 |
| 0.3062 | 2.8754 | 2700 | 0.3263 |
| 0.313 | 2.9819 | 2800 | 0.3259 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.1.2+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1 |