---
license: mit
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
- generated_from_trainer
model-index:
- name: PHI30515HMA2H
  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. -->

# PHI30515HMA2H

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: 0.0643

## 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 7.2249        | 0.09  | 10   | 2.2001          |
| 1.4719        | 0.18  | 20   | 0.3359          |
| 0.3692        | 0.27  | 30   | 0.2930          |
| 0.7802        | 0.36  | 40   | 0.2417          |
| 0.3078        | 0.45  | 50   | 0.2185          |
| 0.4702        | 0.54  | 60   | 0.2195          |
| 0.272         | 0.63  | 70   | 0.1992          |
| 0.2656        | 0.73  | 80   | 0.1711          |
| 0.1386        | 0.82  | 90   | 0.1117          |
| 0.2291        | 0.91  | 100  | 0.1116          |
| 0.1424        | 1.0   | 110  | 0.0853          |
| 0.099         | 1.09  | 120  | 0.1146          |
| 0.1629        | 1.18  | 130  | 0.1753          |
| 0.6955        | 1.27  | 140  | 0.1667          |
| 0.226         | 1.36  | 150  | 0.1119          |
| 0.1085        | 1.45  | 160  | 0.0805          |
| 0.1083        | 1.54  | 170  | 0.0743          |
| 0.2197        | 1.63  | 180  | 0.9735          |
| 0.4915        | 1.72  | 190  | 0.0757          |
| 0.0954        | 1.81  | 200  | 0.0794          |
| 0.0696        | 1.9   | 210  | 0.0698          |
| 0.068         | 1.99  | 220  | 0.0711          |
| 0.0602        | 2.08  | 230  | 0.0702          |
| 0.0896        | 2.18  | 240  | 0.0871          |
| 0.0724        | 2.27  | 250  | 0.0720          |
| 0.0679        | 2.36  | 260  | 0.0688          |
| 0.0764        | 2.45  | 270  | 0.0683          |
| 0.0642        | 2.54  | 280  | 0.0665          |
| 0.058         | 2.63  | 290  | 0.0659          |
| 0.0554        | 2.72  | 300  | 0.0665          |
| 0.0699        | 2.81  | 310  | 0.0654          |
| 0.0752        | 2.9   | 320  | 0.0645          |
| 0.0654        | 2.99  | 330  | 0.0643          |


### Framework versions

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