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---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0309O5
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. -->
# V0309O5
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: 0.0649
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.4836 | 0.09 | 10 | 0.2461 |
| 0.1765 | 0.17 | 20 | 0.1060 |
| 0.1288 | 0.26 | 30 | 0.0855 |
| 0.1098 | 0.34 | 40 | 0.0783 |
| 0.1068 | 0.43 | 50 | 0.0720 |
| 0.0946 | 0.51 | 60 | 0.0751 |
| 0.0852 | 0.6 | 70 | 0.0735 |
| 0.0893 | 0.68 | 80 | 0.0748 |
| 0.0843 | 0.77 | 90 | 0.0690 |
| 0.105 | 0.85 | 100 | 0.0761 |
| 0.0988 | 0.94 | 110 | 0.0738 |
| 0.0928 | 1.02 | 120 | 0.0741 |
| 0.0877 | 1.11 | 130 | 0.0739 |
| 0.0819 | 1.19 | 140 | 0.0731 |
| 0.0808 | 1.28 | 150 | 0.0633 |
| 0.0826 | 1.37 | 160 | 0.0658 |
| 0.0756 | 1.45 | 170 | 0.0711 |
| 0.0726 | 1.54 | 180 | 0.0722 |
| 0.0702 | 1.62 | 190 | 0.0658 |
| 0.0713 | 1.71 | 200 | 0.0666 |
| 0.0755 | 1.79 | 210 | 0.0713 |
| 0.0696 | 1.88 | 220 | 0.0724 |
| 0.0666 | 1.96 | 230 | 0.0709 |
| 0.0644 | 2.05 | 240 | 0.0655 |
| 0.0538 | 2.13 | 250 | 0.0665 |
| 0.0549 | 2.22 | 260 | 0.0702 |
| 0.0494 | 2.3 | 270 | 0.0681 |
| 0.0554 | 2.39 | 280 | 0.0644 |
| 0.0564 | 2.47 | 290 | 0.0647 |
| 0.0538 | 2.56 | 300 | 0.0648 |
| 0.0608 | 2.65 | 310 | 0.0652 |
| 0.0479 | 2.73 | 320 | 0.0649 |
| 0.0505 | 2.82 | 330 | 0.0647 |
| 0.051 | 2.9 | 340 | 0.0651 |
| 0.0523 | 2.99 | 350 | 0.0649 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
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