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---
license: mit
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
- generated_from_trainer
model-index:
- name: Phi0503HMA13
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. -->
# Phi0503HMA13
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: 0.1633
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 4.133 | 0.09 | 10 | 0.8411 |
| 0.4299 | 0.18 | 20 | 0.2571 |
| 0.3825 | 0.27 | 30 | 1.5358 |
| 0.3674 | 0.36 | 40 | 0.1741 |
| 0.1862 | 0.45 | 50 | 0.1464 |
| 0.1476 | 0.54 | 60 | 0.1224 |
| 0.1205 | 0.63 | 70 | 0.1300 |
| 0.1212 | 0.73 | 80 | 0.1016 |
| 0.0941 | 0.82 | 90 | 0.0955 |
| 0.0865 | 0.91 | 100 | 0.0714 |
| 0.1056 | 1.0 | 110 | 2.0855 |
| 0.4121 | 1.09 | 120 | 0.1044 |
| 0.5707 | 1.18 | 130 | 5.1159 |
| 5.3396 | 1.27 | 140 | 4.3182 |
| 2.1029 | 1.36 | 150 | 1.0791 |
| 0.8112 | 1.45 | 160 | 0.4460 |
| 0.3856 | 1.54 | 170 | 0.2762 |
| 0.2282 | 1.63 | 180 | 0.2090 |
| 0.1963 | 1.72 | 190 | 0.1821 |
| 0.2054 | 1.81 | 200 | 0.1859 |
| 0.1811 | 1.9 | 210 | 0.1716 |
| 0.1663 | 1.99 | 220 | 0.1680 |
| 0.1712 | 2.08 | 230 | 0.1657 |
| 0.1649 | 2.18 | 240 | 0.1639 |
| 0.1618 | 2.27 | 250 | 0.1671 |
| 0.1654 | 2.36 | 260 | 0.1642 |
| 0.1621 | 2.45 | 270 | 0.1639 |
| 0.1626 | 2.54 | 280 | 0.1641 |
| 0.1658 | 2.63 | 290 | 0.1640 |
| 0.1657 | 2.72 | 300 | 0.1634 |
| 0.1653 | 2.81 | 310 | 0.1635 |
| 0.1625 | 2.9 | 320 | 0.1633 |
| 0.1674 | 2.99 | 330 | 0.1633 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0
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