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---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0309P3
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. -->
# V0309P3
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: 0.0857
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.9399 | 0.09 | 10 | 0.3747 |
| 0.1877 | 0.17 | 20 | 0.0934 |
| 0.1061 | 0.26 | 30 | 0.0782 |
| 0.0988 | 0.34 | 40 | 0.0751 |
| 0.0879 | 0.43 | 50 | 0.0729 |
| 0.0823 | 0.51 | 60 | 0.0776 |
| 0.0735 | 0.6 | 70 | 0.0698 |
| 0.0775 | 0.68 | 80 | 0.0778 |
| 0.0716 | 0.77 | 90 | 0.0703 |
| 0.0687 | 0.85 | 100 | 0.0701 |
| 0.0718 | 0.94 | 110 | 0.0686 |
| 0.0679 | 1.02 | 120 | 0.0699 |
| 0.0579 | 1.11 | 130 | 0.0769 |
| 0.0559 | 1.19 | 140 | 0.0664 |
| 0.0527 | 1.28 | 150 | 0.0621 |
| 0.05 | 1.37 | 160 | 0.0753 |
| 0.0526 | 1.45 | 170 | 0.0628 |
| 0.0499 | 1.54 | 180 | 0.0685 |
| 0.0487 | 1.62 | 190 | 0.0711 |
| 0.0514 | 1.71 | 200 | 0.0705 |
| 0.0572 | 1.79 | 210 | 0.0724 |
| 0.0487 | 1.88 | 220 | 0.0700 |
| 0.0485 | 1.96 | 230 | 0.0693 |
| 0.0405 | 2.05 | 240 | 0.0706 |
| 0.0338 | 2.13 | 250 | 0.0833 |
| 0.0319 | 2.22 | 260 | 0.0897 |
| 0.0277 | 2.3 | 270 | 0.0941 |
| 0.0351 | 2.39 | 280 | 0.0891 |
| 0.0333 | 2.47 | 290 | 0.0839 |
| 0.0352 | 2.56 | 300 | 0.0867 |
| 0.0357 | 2.65 | 310 | 0.0839 |
| 0.0304 | 2.73 | 320 | 0.0842 |
| 0.0308 | 2.82 | 330 | 0.0859 |
| 0.0291 | 2.9 | 340 | 0.0856 |
| 0.0335 | 2.99 | 350 | 0.0857 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
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