---
license: mit
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
- generated_from_trainer
model-index:
- name: PHI30512HMAB24H
  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. -->

# PHI30512HMAB24H

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: 0.1648

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 4.7682        | 0.09  | 10   | 1.1976          |
| 0.5956        | 0.18  | 20   | 0.2488          |
| 0.3055        | 0.27  | 30   | 0.2493          |
| 0.2386        | 0.36  | 40   | 0.2397          |
| 0.2408        | 0.45  | 50   | 0.2257          |
| 0.2121        | 0.54  | 60   | 1.7294          |
| 0.7562        | 0.63  | 70   | 0.1616          |
| 0.1541        | 0.73  | 80   | 0.1300          |
| 0.2129        | 0.82  | 90   | 0.4410          |
| 4.0055        | 0.91  | 100  | 0.2221          |
| 0.1856        | 1.0   | 110  | 0.2544          |
| 1.5657        | 1.09  | 120  | 6.5436          |
| 4.5499        | 1.18  | 130  | 2.2041          |
| 2.0579        | 1.27  | 140  | 1.1273          |
| 1.0437        | 1.36  | 150  | 0.8327          |
| 0.7015        | 1.45  | 160  | 0.4925          |
| 0.5356        | 1.54  | 170  | 0.4550          |
| 0.3779        | 1.63  | 180  | 0.3327          |
| 0.3294        | 1.72  | 190  | 0.2671          |
| 0.2727        | 1.81  | 200  | 0.2339          |
| 0.2032        | 1.9   | 210  | 0.1869          |
| 0.1883        | 1.99  | 220  | 0.1860          |
| 0.1833        | 2.08  | 230  | 0.1784          |
| 0.1791        | 2.18  | 240  | 0.1742          |
| 0.1737        | 2.27  | 250  | 0.1759          |
| 0.175         | 2.36  | 260  | 0.1742          |
| 0.1724        | 2.45  | 270  | 0.1769          |
| 0.1716        | 2.54  | 280  | 0.1694          |
| 0.1721        | 2.63  | 290  | 0.1694          |
| 0.1693        | 2.72  | 300  | 0.1669          |
| 0.1706        | 2.81  | 310  | 0.1668          |
| 0.1638        | 2.9   | 320  | 0.1649          |
| 0.167         | 2.99  | 330  | 0.1648          |


### Framework versions

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