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---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0424HMA3
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. -->
# V0424HMA3
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: 0.0669
## 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: 80
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.8524 | 0.09 | 10 | 0.4537 |
| 0.1997 | 0.18 | 20 | 0.1136 |
| 0.113 | 0.27 | 30 | 0.0908 |
| 0.0995 | 0.36 | 40 | 0.0755 |
| 0.0777 | 0.45 | 50 | 0.0740 |
| 0.0815 | 0.54 | 60 | 0.0752 |
| 0.0785 | 0.63 | 70 | 0.0753 |
| 0.0849 | 0.73 | 80 | 0.0838 |
| 0.0878 | 0.82 | 90 | 0.0910 |
| 0.0853 | 0.91 | 100 | 0.0737 |
| 0.0807 | 1.0 | 110 | 0.0721 |
| 0.067 | 1.09 | 120 | 0.0745 |
| 0.0718 | 1.18 | 130 | 0.0849 |
| 0.0677 | 1.27 | 140 | 0.0658 |
| 0.0693 | 1.36 | 150 | 0.0678 |
| 0.0711 | 1.45 | 160 | 0.0712 |
| 0.068 | 1.54 | 170 | 0.0707 |
| 0.0687 | 1.63 | 180 | 0.0709 |
| 0.0597 | 1.72 | 190 | 0.0673 |
| 0.065 | 1.81 | 200 | 0.0702 |
| 0.0576 | 1.9 | 210 | 0.0699 |
| 0.0535 | 1.99 | 220 | 0.0610 |
| 0.0382 | 2.08 | 230 | 0.0712 |
| 0.0367 | 2.18 | 240 | 0.0693 |
| 0.0307 | 2.27 | 250 | 0.0662 |
| 0.0311 | 2.36 | 260 | 0.0800 |
| 0.0422 | 2.45 | 270 | 0.0673 |
| 0.0352 | 2.54 | 280 | 0.0661 |
| 0.0305 | 2.63 | 290 | 0.0681 |
| 0.0352 | 2.72 | 300 | 0.0671 |
| 0.0337 | 2.81 | 310 | 0.0672 |
| 0.0333 | 2.9 | 320 | 0.0669 |
| 0.0354 | 2.99 | 330 | 0.0669 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.14.1
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