---
license: mit
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: microsoft/Phi-3-medium-128k-instruct
model-index:
- name: results_medium
  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_medium

This model is a fine-tuned version of [microsoft/Phi-3-medium-128k-instruct](https://huggingface.co/microsoft/Phi-3-medium-128k-instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1562

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 1.9442        | 0.2131 | 100  | 1.9833          |
| 1.8439        | 0.4262 | 200  | 1.8431          |
| 1.5387        | 0.6393 | 300  | 1.5840          |
| 1.4157        | 0.8524 | 400  | 1.3748          |
| 1.2628        | 1.0655 | 500  | 1.2339          |
| 1.2704        | 1.2786 | 600  | 1.1894          |
| 1.1634        | 1.4917 | 700  | 1.1763          |
| 1.2318        | 1.7048 | 800  | 1.1708          |
| 1.0665        | 1.9180 | 900  | 1.1683          |
| 1.1715        | 2.1311 | 1000 | 1.1634          |
| 1.1366        | 2.3442 | 1100 | 1.1617          |
| 1.1239        | 2.5573 | 1200 | 1.1584          |
| 1.1442        | 2.7704 | 1300 | 1.1568          |
| 1.1336        | 2.9835 | 1400 | 1.1562          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1