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---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0415MA1
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. -->
# V0415MA1
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: 0.0598
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 2.2693 | 0.09 | 10 | 1.1034 |
| 0.5007 | 0.18 | 20 | 0.1183 |
| 0.1243 | 0.27 | 30 | 0.1078 |
| 0.1244 | 0.36 | 40 | 0.0970 |
| 0.0995 | 0.45 | 50 | 0.0818 |
| 0.0931 | 0.54 | 60 | 0.0755 |
| 0.0789 | 0.63 | 70 | 0.0721 |
| 0.0772 | 0.73 | 80 | 0.0731 |
| 0.0799 | 0.82 | 90 | 0.0635 |
| 0.0756 | 0.91 | 100 | 0.0640 |
| 0.072 | 1.0 | 110 | 0.0657 |
| 0.064 | 1.09 | 120 | 0.0627 |
| 0.0616 | 1.18 | 130 | 0.0610 |
| 0.0587 | 1.27 | 140 | 0.0618 |
| 0.0569 | 1.36 | 150 | 0.0604 |
| 0.0652 | 1.45 | 160 | 0.0624 |
| 0.0617 | 1.54 | 170 | 0.0605 |
| 0.0633 | 1.63 | 180 | 0.0578 |
| 0.0607 | 1.72 | 190 | 0.0573 |
| 0.0673 | 1.81 | 200 | 0.0626 |
| 0.0553 | 1.9 | 210 | 0.0661 |
| 0.055 | 1.99 | 220 | 0.0647 |
| 0.0433 | 2.08 | 230 | 0.0773 |
| 0.0466 | 2.18 | 240 | 0.0589 |
| 0.0429 | 2.27 | 250 | 0.0684 |
| 0.0408 | 2.36 | 260 | 0.0617 |
| 0.0421 | 2.45 | 270 | 0.0640 |
| 0.0389 | 2.54 | 280 | 0.0633 |
| 0.0431 | 2.63 | 290 | 0.0594 |
| 0.0429 | 2.72 | 300 | 0.0616 |
| 0.0431 | 2.81 | 310 | 0.0616 |
| 0.0434 | 2.9 | 320 | 0.0604 |
| 0.046 | 2.99 | 330 | 0.0598 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
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