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---
license: mit
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
- generated_from_trainer
model-index:
- name: Phi30513MA
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. -->
# Phi30513MA
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: 0.0792
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 4.162 | 0.09 | 10 | 2.1516 |
| 1.0891 | 0.18 | 20 | 0.3958 |
| 0.2412 | 0.27 | 30 | 0.1475 |
| 0.1456 | 0.36 | 40 | 0.1307 |
| 0.127 | 0.45 | 50 | 0.1272 |
| 0.1169 | 0.54 | 60 | 0.0964 |
| 0.0967 | 0.63 | 70 | 0.0978 |
| 0.0887 | 0.73 | 80 | 0.0936 |
| 0.0807 | 0.82 | 90 | 0.0875 |
| 0.0837 | 0.91 | 100 | 0.0734 |
| 0.0758 | 1.0 | 110 | 0.0739 |
| 0.0614 | 1.09 | 120 | 0.0710 |
| 0.0552 | 1.18 | 130 | 0.0801 |
| 0.0579 | 1.27 | 140 | 0.0727 |
| 0.0561 | 1.36 | 150 | 0.0691 |
| 0.0616 | 1.45 | 160 | 0.0688 |
| 0.0566 | 1.54 | 170 | 0.0676 |
| 0.0519 | 1.63 | 180 | 0.0681 |
| 0.0514 | 1.72 | 190 | 0.0678 |
| 0.0602 | 1.81 | 200 | 0.0634 |
| 0.0466 | 1.9 | 210 | 0.0660 |
| 0.0481 | 1.99 | 220 | 0.0692 |
| 0.0325 | 2.08 | 230 | 0.0737 |
| 0.0358 | 2.18 | 240 | 0.0797 |
| 0.0265 | 2.27 | 250 | 0.0851 |
| 0.0299 | 2.36 | 260 | 0.0870 |
| 0.0337 | 2.45 | 270 | 0.0826 |
| 0.0292 | 2.54 | 280 | 0.0812 |
| 0.0303 | 2.63 | 290 | 0.0813 |
| 0.0356 | 2.72 | 300 | 0.0799 |
| 0.0358 | 2.81 | 310 | 0.0795 |
| 0.0387 | 2.9 | 320 | 0.0792 |
| 0.0313 | 2.99 | 330 | 0.0792 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0
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