---
license: mit
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
- generated_from_trainer
model-index:
- name: Phi0503HMA6
  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. -->

# Phi0503HMA6

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: 0.1670

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 4.2469        | 0.09  | 10   | 0.9109          |
| 0.4285        | 0.18  | 20   | 0.2506          |
| 0.266         | 0.27  | 30   | 0.2427          |
| 0.2313        | 0.36  | 40   | 0.2118          |
| 0.1808        | 0.45  | 50   | 0.1604          |
| 0.163         | 0.54  | 60   | 0.1760          |
| 0.2571        | 0.63  | 70   | 0.1448          |
| 0.2789        | 0.73  | 80   | 0.1488          |
| 0.7096        | 0.82  | 90   | 1.2197          |
| 1.051         | 0.91  | 100  | 1.2133          |
| 0.4623        | 1.0   | 110  | 4.9980          |
| 4.8479        | 1.09  | 120  | 2.3085          |
| 1.6873        | 1.18  | 130  | 0.7471          |
| 0.5896        | 1.27  | 140  | 0.3693          |
| 0.334         | 1.36  | 150  | 0.2707          |
| 0.2556        | 1.45  | 160  | 0.2347          |
| 0.2087        | 1.54  | 170  | 0.1840          |
| 0.187         | 1.63  | 180  | 0.1858          |
| 0.1833        | 1.72  | 190  | 0.1842          |
| 0.1755        | 1.81  | 200  | 0.1787          |
| 0.1772        | 1.9   | 210  | 0.1708          |
| 0.1698        | 1.99  | 220  | 0.1714          |
| 0.1723        | 2.08  | 230  | 0.1691          |
| 0.1674        | 2.18  | 240  | 0.1693          |
| 0.1682        | 2.27  | 250  | 0.1709          |
| 0.1684        | 2.36  | 260  | 0.1702          |
| 0.166         | 2.45  | 270  | 0.1681          |
| 0.1651        | 2.54  | 280  | 0.1683          |
| 0.1689        | 2.63  | 290  | 0.1688          |
| 0.17          | 2.72  | 300  | 0.1675          |
| 0.1696        | 2.81  | 310  | 0.1674          |
| 0.1663        | 2.9   | 320  | 0.1670          |
| 0.1712        | 2.99  | 330  | 0.1670          |


### Framework versions

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