---
license: mit
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
- generated_from_trainer
model-index:
- name: PHI30512HMAB1H
  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. -->

# PHI30512HMAB1H

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: 0.0701

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 5.2344        | 0.09  | 10   | 2.7793          |
| 1.4671        | 0.18  | 20   | 0.5131          |
| 0.3676        | 0.27  | 30   | 2.8781          |
| 0.907         | 0.36  | 40   | 0.2773          |
| 0.2875        | 0.45  | 50   | 0.2421          |
| 0.2486        | 0.54  | 60   | 0.2263          |
| 0.168         | 0.63  | 70   | 0.1595          |
| 0.1505        | 0.73  | 80   | 0.1210          |
| 0.1137        | 0.82  | 90   | 0.1122          |
| 0.1072        | 0.91  | 100  | 0.0915          |
| 0.0906        | 1.0   | 110  | 0.0853          |
| 0.0752        | 1.09  | 120  | 0.0731          |
| 0.0625        | 1.18  | 130  | 0.0723          |
| 0.0649        | 1.27  | 140  | 0.0678          |
| 0.0563        | 1.36  | 150  | 0.0720          |
| 0.0656        | 1.45  | 160  | 0.0662          |
| 0.0638        | 1.54  | 170  | 0.0649          |
| 0.0603        | 1.63  | 180  | 0.0649          |
| 0.0537        | 1.72  | 190  | 0.0626          |
| 0.0638        | 1.81  | 200  | 0.0605          |
| 0.0523        | 1.9   | 210  | 0.0721          |
| 0.0637        | 1.99  | 220  | 0.0634          |
| 0.0384        | 2.08  | 230  | 0.0658          |
| 0.0345        | 2.18  | 240  | 0.0741          |
| 0.0292        | 2.27  | 250  | 0.0753          |
| 0.0323        | 2.36  | 260  | 0.0699          |
| 0.0378        | 2.45  | 270  | 0.0669          |
| 0.0304        | 2.54  | 280  | 0.0712          |
| 0.032         | 2.63  | 290  | 0.0713          |
| 0.0351        | 2.72  | 300  | 0.0706          |
| 0.0388        | 2.81  | 310  | 0.0706          |
| 0.035         | 2.9   | 320  | 0.0697          |
| 0.0318        | 2.99  | 330  | 0.0701          |


### Framework versions

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