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license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0422MADP6C
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. -->
# V0422MADP6C
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: 0.0637
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 5.2356 | 0.09 | 10 | 1.9434 |
| 2.8956 | 0.18 | 20 | 0.1595 |
| 0.6107 | 0.27 | 30 | 0.1437 |
| 0.1936 | 0.36 | 40 | 0.1236 |
| 0.1283 | 0.45 | 50 | 0.1001 |
| 0.1141 | 0.54 | 60 | 0.0983 |
| 0.1042 | 0.63 | 70 | 0.0888 |
| 0.089 | 0.73 | 80 | 0.0854 |
| 0.0922 | 0.82 | 90 | 0.0815 |
| 0.0892 | 0.91 | 100 | 0.0750 |
| 0.0853 | 1.0 | 110 | 0.0789 |
| 0.0755 | 1.09 | 120 | 0.0722 |
| 0.0795 | 1.18 | 130 | 0.0764 |
| 0.0794 | 1.27 | 140 | 0.0783 |
| 0.0711 | 1.36 | 150 | 0.0753 |
| 0.0717 | 1.45 | 160 | 0.0720 |
| 0.067 | 1.54 | 170 | 0.0739 |
| 0.0688 | 1.63 | 180 | 0.0712 |
| 0.0654 | 1.72 | 190 | 0.0699 |
| 0.0694 | 1.81 | 200 | 0.0652 |
| 0.0621 | 1.9 | 210 | 0.0680 |
| 0.0661 | 1.99 | 220 | 0.0654 |
| 0.0515 | 2.08 | 230 | 0.0617 |
| 0.0513 | 2.18 | 240 | 0.0650 |
| 0.0462 | 2.27 | 250 | 0.0725 |
| 0.0491 | 2.36 | 260 | 0.0693 |
| 0.0538 | 2.45 | 270 | 0.0697 |
| 0.0507 | 2.54 | 280 | 0.0663 |
| 0.0437 | 2.63 | 290 | 0.0642 |
| 0.0489 | 2.72 | 300 | 0.0635 |
| 0.0485 | 2.81 | 310 | 0.0637 |
| 0.0456 | 2.9 | 320 | 0.0637 |
| 0.0557 | 2.99 | 330 | 0.0637 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.14.1
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