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---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0424HMA14
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. -->
# V0424HMA14
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: 0.0630
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.8628 | 0.09 | 10 | 0.5176 |
| 0.2396 | 0.18 | 20 | 0.1179 |
| 0.1148 | 0.27 | 30 | 0.0892 |
| 0.0925 | 0.36 | 40 | 0.0789 |
| 0.0835 | 0.45 | 50 | 0.0734 |
| 0.0872 | 0.54 | 60 | 0.0735 |
| 0.0757 | 0.63 | 70 | 0.0710 |
| 0.0728 | 0.73 | 80 | 0.0907 |
| 0.0898 | 0.82 | 90 | 0.0746 |
| 0.0858 | 0.91 | 100 | 0.0731 |
| 0.0852 | 1.0 | 110 | 0.0704 |
| 0.0589 | 1.09 | 120 | 0.0979 |
| 0.0715 | 1.18 | 130 | 0.0719 |
| 0.0714 | 1.27 | 140 | 0.0681 |
| 0.0674 | 1.36 | 150 | 0.0717 |
| 0.0745 | 1.45 | 160 | 0.0693 |
| 0.0691 | 1.54 | 170 | 0.0694 |
| 0.0733 | 1.63 | 180 | 0.0658 |
| 0.0598 | 1.72 | 190 | 0.0676 |
| 0.0683 | 1.81 | 200 | 0.0714 |
| 0.058 | 1.9 | 210 | 0.0663 |
| 0.0565 | 1.99 | 220 | 0.0635 |
| 0.0393 | 2.08 | 230 | 0.0740 |
| 0.0355 | 2.18 | 240 | 0.0752 |
| 0.0386 | 2.27 | 250 | 0.0688 |
| 0.0347 | 2.36 | 260 | 0.0681 |
| 0.0365 | 2.45 | 270 | 0.0675 |
| 0.034 | 2.54 | 280 | 0.0671 |
| 0.0307 | 2.63 | 290 | 0.0637 |
| 0.0326 | 2.72 | 300 | 0.0629 |
| 0.0351 | 2.81 | 310 | 0.0633 |
| 0.0302 | 2.9 | 320 | 0.0631 |
| 0.0337 | 2.99 | 330 | 0.0630 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
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