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---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0424HMA21
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. -->
# V0424HMA21
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: 0.0510
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.7087 | 0.09 | 10 | 0.1473 |
| 0.1506 | 0.18 | 20 | 0.1108 |
| 0.1133 | 0.27 | 30 | 0.1019 |
| 0.1011 | 0.36 | 40 | 0.0782 |
| 0.0812 | 0.45 | 50 | 0.0733 |
| 0.0826 | 0.54 | 60 | 0.0711 |
| 0.078 | 0.63 | 70 | 0.0749 |
| 0.0795 | 0.73 | 80 | 0.0884 |
| 0.0828 | 0.82 | 90 | 0.0764 |
| 0.0862 | 0.91 | 100 | 0.2925 |
| 0.139 | 1.0 | 110 | 0.0806 |
| 0.0759 | 1.09 | 120 | 0.1017 |
| 0.1034 | 1.18 | 130 | 0.0768 |
| 0.0777 | 1.27 | 140 | 0.0675 |
| 0.0737 | 1.36 | 150 | 0.0729 |
| 0.0768 | 1.45 | 160 | 0.0766 |
| 0.0768 | 1.54 | 170 | 0.0676 |
| 0.0689 | 1.63 | 180 | 0.0659 |
| 0.0599 | 1.72 | 190 | 0.0638 |
| 0.0599 | 1.81 | 200 | 0.0603 |
| 0.0503 | 1.9 | 210 | 0.0587 |
| 0.0444 | 1.99 | 220 | 0.0525 |
| 0.0275 | 2.08 | 230 | 0.0535 |
| 0.0215 | 2.18 | 240 | 0.0584 |
| 0.0207 | 2.27 | 250 | 0.0554 |
| 0.0205 | 2.36 | 260 | 0.0547 |
| 0.0244 | 2.45 | 270 | 0.0533 |
| 0.023 | 2.54 | 280 | 0.0511 |
| 0.0192 | 2.63 | 290 | 0.0521 |
| 0.0183 | 2.72 | 300 | 0.0516 |
| 0.0236 | 2.81 | 310 | 0.0512 |
| 0.0212 | 2.9 | 320 | 0.0510 |
| 0.0189 | 2.99 | 330 | 0.0510 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
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