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---
license: mit
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
- generated_from_trainer
model-index:
- name: PHI30512HMAB18H
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. -->
# PHI30512HMAB18H
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: 0.0740
## 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: 60
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 4.2497 | 0.09 | 10 | 0.9067 |
| 0.4537 | 0.18 | 20 | 0.2641 |
| 0.3338 | 0.27 | 30 | 0.2501 |
| 0.2554 | 0.36 | 40 | 0.2343 |
| 0.2601 | 0.45 | 50 | 0.2149 |
| 0.2187 | 0.54 | 60 | 0.2108 |
| 0.2111 | 0.63 | 70 | 0.2032 |
| 0.1904 | 0.73 | 80 | 0.1720 |
| 0.1685 | 0.82 | 90 | 0.1673 |
| 0.1626 | 0.91 | 100 | 0.1636 |
| 0.1578 | 1.0 | 110 | 0.1104 |
| 0.1041 | 1.09 | 120 | 0.0870 |
| 0.0882 | 1.18 | 130 | 0.0854 |
| 0.0933 | 1.27 | 140 | 0.0801 |
| 0.0816 | 1.36 | 150 | 0.0792 |
| 0.0829 | 1.45 | 160 | 0.0751 |
| 0.0741 | 1.54 | 170 | 0.0777 |
| 0.0773 | 1.63 | 180 | 0.0732 |
| 0.0705 | 1.72 | 190 | 0.0705 |
| 0.0749 | 1.81 | 200 | 0.0677 |
| 0.0624 | 1.9 | 210 | 0.0734 |
| 0.0655 | 1.99 | 220 | 0.0722 |
| 0.0436 | 2.08 | 230 | 0.0802 |
| 0.0464 | 2.18 | 240 | 0.0876 |
| 0.0402 | 2.27 | 250 | 0.0758 |
| 0.0379 | 2.36 | 260 | 0.0742 |
| 0.0435 | 2.45 | 270 | 0.0732 |
| 0.0348 | 2.54 | 280 | 0.0766 |
| 0.0356 | 2.63 | 290 | 0.0775 |
| 0.0409 | 2.72 | 300 | 0.0757 |
| 0.0473 | 2.81 | 310 | 0.0746 |
| 0.0401 | 2.9 | 320 | 0.0741 |
| 0.0402 | 2.99 | 330 | 0.0740 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0
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