---
license: mit
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
- generated_from_trainer
model-index:
- name: PHI30512HMAB2H
  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. -->

# PHI30512HMAB2H

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: 0.0778

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 5.1146        | 0.09  | 10   | 2.3492          |
| 1.1333        | 0.18  | 20   | 0.3905          |
| 0.7088        | 0.27  | 30   | 0.3297          |
| 0.2795        | 0.36  | 40   | 0.2609          |
| 0.2615        | 0.45  | 50   | 0.2361          |
| 0.2203        | 0.54  | 60   | 0.2194          |
| 0.2338        | 0.63  | 70   | 0.2381          |
| 0.2231        | 0.73  | 80   | 0.1473          |
| 0.3939        | 0.82  | 90   | 0.2078          |
| 0.1899        | 0.91  | 100  | 0.1756          |
| 0.1743        | 1.0   | 110  | 0.1207          |
| 0.1234        | 1.09  | 120  | 0.1252          |
| 0.0985        | 1.18  | 130  | 0.0798          |
| 0.1583        | 1.27  | 140  | 0.0846          |
| 0.1099        | 1.36  | 150  | 0.1042          |
| 0.1727        | 1.45  | 160  | 0.1675          |
| 0.1701        | 1.54  | 170  | 0.1622          |
| 0.1069        | 1.63  | 180  | 0.0767          |
| 0.0735        | 1.72  | 190  | 0.0767          |
| 0.12          | 1.81  | 200  | 0.5347          |
| 0.3029        | 1.9   | 210  | 0.0825          |
| 0.0712        | 1.99  | 220  | 0.0767          |
| 0.0669        | 2.08  | 230  | 0.9840          |
| 0.2695        | 2.18  | 240  | 0.5707          |
| 0.385         | 2.27  | 250  | 0.1643          |
| 0.1644        | 2.36  | 260  | 0.1611          |
| 0.1309        | 2.45  | 270  | 0.0754          |
| 0.0609        | 2.54  | 280  | 0.0761          |
| 0.0719        | 2.63  | 290  | 0.0951          |
| 0.0886        | 2.72  | 300  | 0.0872          |
| 0.0838        | 2.81  | 310  | 0.0797          |
| 0.0698        | 2.9   | 320  | 0.0779          |
| 0.0735        | 2.99  | 330  | 0.0778          |


### Framework versions

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