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---
license: mit
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
- generated_from_trainer
model-index:
- name: PHI30515HMA1H
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. -->
# PHI30515HMA1H
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: 0.0747
## 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 7.2832 | 0.09 | 10 | 2.7337 |
| 1.7648 | 0.18 | 20 | 0.3745 |
| 0.3839 | 0.27 | 30 | 0.2589 |
| 0.3285 | 0.36 | 40 | 0.2520 |
| 0.3202 | 0.45 | 50 | 0.2229 |
| 0.6502 | 0.54 | 60 | 0.2693 |
| 0.3048 | 0.63 | 70 | 0.1647 |
| 0.2068 | 0.73 | 80 | 0.1318 |
| 0.1411 | 0.82 | 90 | 0.1621 |
| 0.1775 | 0.91 | 100 | 0.0975 |
| 0.1835 | 1.0 | 110 | 0.0954 |
| 0.1014 | 1.09 | 120 | 0.0876 |
| 0.1148 | 1.18 | 130 | 0.0976 |
| 0.1506 | 1.27 | 140 | 0.0760 |
| 0.128 | 1.36 | 150 | 0.0750 |
| 0.0883 | 1.45 | 160 | 0.0736 |
| 0.0913 | 1.54 | 170 | 0.0692 |
| 0.0795 | 1.63 | 180 | 0.0681 |
| 0.0927 | 1.72 | 190 | 0.0669 |
| 0.087 | 1.81 | 200 | 0.0667 |
| 0.0606 | 1.9 | 210 | 0.0682 |
| 0.0627 | 1.99 | 220 | 0.0679 |
| 0.0441 | 2.08 | 230 | 0.0705 |
| 0.0543 | 2.18 | 240 | 0.0813 |
| 0.0413 | 2.27 | 250 | 0.0839 |
| 0.0414 | 2.36 | 260 | 0.0775 |
| 0.0462 | 2.45 | 270 | 0.0756 |
| 0.0411 | 2.54 | 280 | 0.0763 |
| 0.0392 | 2.63 | 290 | 0.0768 |
| 0.0407 | 2.72 | 300 | 0.0771 |
| 0.0508 | 2.81 | 310 | 0.0755 |
| 0.0577 | 2.9 | 320 | 0.0746 |
| 0.0431 | 2.99 | 330 | 0.0747 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0
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