---
license: mit
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
- generated_from_trainer
model-index:
- name: Phi0503HMA13
  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. -->

# Phi0503HMA13

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: 0.1500

## 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: 100
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 4.3182        | 0.09  | 10   | 0.7624          |
| 0.4834        | 0.18  | 20   | 1.2058          |
| 0.3549        | 0.27  | 30   | 0.2669          |
| 0.2274        | 0.36  | 40   | 0.2185          |
| 0.2285        | 0.45  | 50   | 0.2200          |
| 0.2479        | 0.54  | 60   | 0.1945          |
| 0.1659        | 0.63  | 70   | 0.1633          |
| 0.1503        | 0.73  | 80   | 0.1265          |
| 0.1177        | 0.82  | 90   | 0.1423          |
| 0.1198        | 0.91  | 100  | 0.0903          |
| 0.0947        | 1.0   | 110  | 0.1087          |
| 0.1089        | 1.09  | 120  | 0.0931          |
| 0.1213        | 1.18  | 130  | 4.1813          |
| 4.4675        | 1.27  | 140  | 3.9663          |
| 2.1661        | 1.36  | 150  | 1.0762          |
| 0.8392        | 1.45  | 160  | 0.6845          |
| 0.4289        | 1.54  | 170  | 0.3521          |
| 0.352         | 1.63  | 180  | 0.3356          |
| 0.307         | 1.72  | 190  | 0.3067          |
| 0.3166        | 1.81  | 200  | 0.2883          |
| 0.2595        | 1.9   | 210  | 0.2330          |
| 0.2175        | 1.99  | 220  | 0.2074          |
| 0.1936        | 2.08  | 230  | 0.1947          |
| 0.1876        | 2.18  | 240  | 0.1737          |
| 0.1734        | 2.27  | 250  | 0.1709          |
| 0.1679        | 2.36  | 260  | 0.1631          |
| 0.1624        | 2.45  | 270  | 0.1630          |
| 0.1606        | 2.54  | 280  | 0.1582          |
| 0.1601        | 2.63  | 290  | 0.1574          |
| 0.1592        | 2.72  | 300  | 0.1542          |
| 0.1569        | 2.81  | 310  | 0.1519          |
| 0.1509        | 2.9   | 320  | 0.1505          |
| 0.1527        | 2.99  | 330  | 0.1500          |


### Framework versions

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