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---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0309P5
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. -->
# V0309P5
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: 0.0741
## 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: 20
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.592 | 0.09 | 10 | 0.1275 |
| 0.1268 | 0.17 | 20 | 0.0836 |
| 0.099 | 0.26 | 30 | 0.0700 |
| 0.093 | 0.34 | 40 | 0.0736 |
| 0.0889 | 0.43 | 50 | 0.0646 |
| 0.0878 | 0.51 | 60 | 0.0700 |
| 0.0796 | 0.6 | 70 | 0.0625 |
| 0.0821 | 0.68 | 80 | 0.0669 |
| 0.0779 | 0.77 | 90 | 0.0583 |
| 0.0967 | 0.85 | 100 | 0.0651 |
| 0.0865 | 0.94 | 110 | 0.0666 |
| 0.0848 | 1.02 | 120 | 0.0683 |
| 0.0741 | 1.11 | 130 | 0.0682 |
| 0.0681 | 1.19 | 140 | 0.0677 |
| 0.0682 | 1.28 | 150 | 0.0653 |
| 0.0671 | 1.37 | 160 | 0.0641 |
| 0.064 | 1.45 | 170 | 0.0612 |
| 0.0608 | 1.54 | 180 | 0.0638 |
| 0.0626 | 1.62 | 190 | 0.0608 |
| 0.0641 | 1.71 | 200 | 0.0619 |
| 0.0658 | 1.79 | 210 | 0.0661 |
| 0.0606 | 1.88 | 220 | 0.0650 |
| 0.0571 | 1.96 | 230 | 0.0630 |
| 0.0501 | 2.05 | 240 | 0.0731 |
| 0.0412 | 2.13 | 250 | 0.0798 |
| 0.0418 | 2.22 | 260 | 0.0809 |
| 0.0385 | 2.3 | 270 | 0.0767 |
| 0.0433 | 2.39 | 280 | 0.0723 |
| 0.043 | 2.47 | 290 | 0.0710 |
| 0.0411 | 2.56 | 300 | 0.0739 |
| 0.0468 | 2.65 | 310 | 0.0740 |
| 0.037 | 2.73 | 320 | 0.0732 |
| 0.0398 | 2.82 | 330 | 0.0741 |
| 0.0405 | 2.9 | 340 | 0.0740 |
| 0.0415 | 2.99 | 350 | 0.0741 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
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