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---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0417MADP4
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. -->
# V0417MADP4
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: 0.1454
## 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: 60
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 8.3437 | 0.09 | 10 | 2.9727 |
| 6.7169 | 0.18 | 20 | 2.7571 |
| 4.7246 | 0.27 | 30 | 2.3872 |
| 2.7752 | 0.36 | 40 | 1.7401 |
| 1.361 | 0.45 | 50 | 1.0587 |
| 0.6269 | 0.54 | 60 | 0.6595 |
| 0.333 | 0.63 | 70 | 0.3442 |
| 0.2172 | 0.73 | 80 | 0.2248 |
| 0.1846 | 0.82 | 90 | 0.2079 |
| 0.1761 | 0.91 | 100 | 0.1780 |
| 0.1761 | 1.0 | 110 | 0.1788 |
| 0.171 | 1.09 | 120 | 0.1687 |
| 0.161 | 1.18 | 130 | 0.1565 |
| 0.1566 | 1.27 | 140 | 0.1558 |
| 0.2021 | 1.36 | 150 | 0.1842 |
| 0.1681 | 1.45 | 160 | 0.1545 |
| 0.1668 | 1.54 | 170 | 0.1516 |
| 0.1642 | 1.63 | 180 | 0.1501 |
| 0.1685 | 1.72 | 190 | 0.1599 |
| 0.1685 | 1.81 | 200 | 0.1543 |
| 0.1643 | 1.9 | 210 | 0.1679 |
| 0.1608 | 1.99 | 220 | 0.1575 |
| 0.1593 | 2.08 | 230 | 0.1475 |
| 0.1539 | 2.18 | 240 | 0.1490 |
| 0.1511 | 2.27 | 250 | 0.1463 |
| 0.1543 | 2.36 | 260 | 0.1468 |
| 0.1534 | 2.45 | 270 | 0.1477 |
| 0.1524 | 2.54 | 280 | 0.1462 |
| 0.1513 | 2.63 | 290 | 0.1457 |
| 0.153 | 2.72 | 300 | 0.1457 |
| 0.1516 | 2.81 | 310 | 0.1454 |
| 0.153 | 2.9 | 320 | 0.1454 |
| 0.1535 | 2.99 | 330 | 0.1454 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
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