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---
license: mit
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
- generated_from_trainer
model-index:
- name: Phi0503HMA8
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. -->
# Phi0503HMA8
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: 0.1630
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 4.6142 | 0.09 | 10 | 1.3143 |
| 0.5476 | 0.18 | 20 | 0.2468 |
| 0.3629 | 0.27 | 30 | 0.2346 |
| 0.2414 | 0.36 | 40 | 0.2269 |
| 0.2169 | 0.45 | 50 | 0.1917 |
| 0.1925 | 0.54 | 60 | 0.1844 |
| 0.1977 | 0.63 | 70 | 0.1833 |
| 0.1755 | 0.73 | 80 | 0.1650 |
| 0.1689 | 0.82 | 90 | 0.1627 |
| 0.1552 | 0.91 | 100 | 0.7844 |
| 0.2892 | 1.0 | 110 | 0.1149 |
| 1.1144 | 1.09 | 120 | 0.1357 |
| 0.1033 | 1.18 | 130 | 0.0829 |
| 0.098 | 1.27 | 140 | 0.0898 |
| 0.0863 | 1.36 | 150 | 0.0845 |
| 0.0913 | 1.45 | 160 | 0.0791 |
| 0.0782 | 1.54 | 170 | 0.0708 |
| 0.0804 | 1.63 | 180 | 0.0786 |
| 0.089 | 1.72 | 190 | 0.2288 |
| 0.3087 | 1.81 | 200 | 0.1845 |
| 0.449 | 1.9 | 210 | 0.3669 |
| 0.7395 | 1.99 | 220 | 0.3523 |
| 0.5132 | 2.08 | 230 | 0.1956 |
| 0.1939 | 2.18 | 240 | 0.1647 |
| 0.1612 | 2.27 | 250 | 0.1673 |
| 0.1638 | 2.36 | 260 | 0.1636 |
| 0.1617 | 2.45 | 270 | 0.1634 |
| 0.1617 | 2.54 | 280 | 0.1640 |
| 0.1626 | 2.63 | 290 | 0.1641 |
| 0.1635 | 2.72 | 300 | 0.1634 |
| 0.1638 | 2.81 | 310 | 0.1632 |
| 0.162 | 2.9 | 320 | 0.1630 |
| 0.1659 | 2.99 | 330 | 0.1630 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0
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