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---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0424HMA15
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. -->
# V0424HMA15
This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0650
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.7205 | 0.09 | 10 | 0.3362 |
| 0.1955 | 0.18 | 20 | 0.1154 |
| 0.1119 | 0.27 | 30 | 0.0882 |
| 0.0909 | 0.36 | 40 | 0.0772 |
| 0.0819 | 0.45 | 50 | 0.0712 |
| 0.0876 | 0.54 | 60 | 0.0683 |
| 0.0753 | 0.63 | 70 | 0.0674 |
| 0.0739 | 0.73 | 80 | 0.0799 |
| 0.0803 | 0.82 | 90 | 0.0730 |
| 0.0825 | 0.91 | 100 | 0.0692 |
| 0.0813 | 1.0 | 110 | 0.0643 |
| 0.0612 | 1.09 | 120 | 0.0723 |
| 0.0638 | 1.18 | 130 | 0.0743 |
| 0.0646 | 1.27 | 140 | 0.0638 |
| 0.0639 | 1.36 | 150 | 0.0671 |
| 0.0704 | 1.45 | 160 | 0.0774 |
| 0.0672 | 1.54 | 170 | 0.0651 |
| 0.0703 | 1.63 | 180 | 0.0635 |
| 0.057 | 1.72 | 190 | 0.0654 |
| 0.0644 | 1.81 | 200 | 0.0719 |
| 0.0563 | 1.9 | 210 | 0.0721 |
| 0.0588 | 1.99 | 220 | 0.0646 |
| 0.035 | 2.08 | 230 | 0.0914 |
| 0.0409 | 2.18 | 240 | 0.0654 |
| 0.0366 | 2.27 | 250 | 0.0682 |
| 0.0333 | 2.36 | 260 | 0.0752 |
| 0.0356 | 2.45 | 270 | 0.0696 |
| 0.0298 | 2.54 | 280 | 0.0685 |
| 0.0294 | 2.63 | 290 | 0.0672 |
| 0.034 | 2.72 | 300 | 0.0656 |
| 0.0345 | 2.81 | 310 | 0.0652 |
| 0.0318 | 2.9 | 320 | 0.0650 |
| 0.0354 | 2.99 | 330 | 0.0650 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
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