---
license: mit
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
- generated_from_trainer
model-index:
- name: PHI30512HMAB22H
  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. -->

# PHI30512HMAB22H

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: 0.0375

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 80
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 4.9533        | 0.09  | 10   | 1.5870          |
| 0.7577        | 0.18  | 20   | 0.2615          |
| 0.2902        | 0.27  | 30   | 0.2473          |
| 0.2709        | 0.36  | 40   | 0.2446          |
| 0.26          | 0.45  | 50   | 0.2296          |
| 0.2324        | 0.54  | 60   | 0.2222          |
| 0.2278        | 0.63  | 70   | 0.2435          |
| 0.236         | 0.73  | 80   | 0.2284          |
| 0.1862        | 0.82  | 90   | 0.1793          |
| 0.1768        | 0.91  | 100  | 0.1645          |
| 0.1688        | 1.0   | 110  | 0.1509          |
| 0.1331        | 1.09  | 120  | 0.1000          |
| 0.0923        | 1.18  | 130  | 0.1010          |
| 0.097         | 1.27  | 140  | 0.0757          |
| 0.0803        | 1.36  | 150  | 0.0747          |
| 0.0813        | 1.45  | 160  | 0.0709          |
| 0.0747        | 1.54  | 170  | 0.0715          |
| 0.0726        | 1.63  | 180  | 0.0665          |
| 0.0678        | 1.72  | 190  | 0.0680          |
| 0.0692        | 1.81  | 200  | 0.0700          |
| 0.0607        | 1.9   | 210  | 0.0704          |
| 0.064         | 1.99  | 220  | 0.0667          |
| 0.0417        | 2.08  | 230  | 0.0758          |
| 0.0415        | 2.18  | 240  | 0.0743          |
| 0.0356        | 2.27  | 250  | 0.0644          |
| 0.0321        | 2.36  | 260  | 0.0600          |
| 0.0365        | 2.45  | 270  | 0.0490          |
| 0.0255        | 2.54  | 280  | 0.0453          |
| 0.0239        | 2.63  | 290  | 0.0437          |
| 0.0299        | 2.72  | 300  | 0.0404          |
| 0.0262        | 2.81  | 310  | 0.0394          |
| 0.0239        | 2.9   | 320  | 0.0375          |
| 0.0271        | 2.99  | 330  | 0.0375          |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0