---
base_model: microsoft/Phi-3-mini-4k-instruct
library_name: peft
license: mit
tags:
- trl
- sft
- generated_from_trainer
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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/tarunwandb/huggingface/runs/5mqa1xeb)
# results

This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2406

## 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: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.2518        | 0.0530 | 100  | 1.3453          |
| 1.3137        | 0.1059 | 200  | 1.2820          |
| 1.2681        | 0.1589 | 300  | 1.2684          |
| 1.2611        | 0.2118 | 400  | 1.2625          |
| 1.2599        | 0.2648 | 500  | 1.2587          |
| 1.2709        | 0.3177 | 600  | 1.2561          |
| 1.2607        | 0.3707 | 700  | 1.2537          |
| 1.2502        | 0.4236 | 800  | 1.2515          |
| 1.2475        | 0.4766 | 900  | 1.2494          |
| 1.2479        | 0.5295 | 1000 | 1.2476          |
| 1.2535        | 0.5825 | 1100 | 1.2469          |
| 1.2546        | 0.6354 | 1200 | 1.2455          |
| 1.2498        | 0.6884 | 1300 | 1.2440          |
| 1.2445        | 0.7413 | 1400 | 1.2433          |
| 1.247         | 0.7943 | 1500 | 1.2423          |
| 1.2438        | 0.8472 | 1600 | 1.2418          |
| 1.2434        | 0.9002 | 1700 | 1.2413          |
| 1.2425        | 0.9531 | 1800 | 1.2406          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1