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---
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0422MADP2
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. -->
# V0422MADP2
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: 0.0322
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.9195 | 0.09 | 10 | 0.9281 |
| 0.2943 | 0.18 | 20 | 0.1207 |
| 0.1134 | 0.27 | 30 | 0.0961 |
| 0.1076 | 0.36 | 40 | 0.0790 |
| 0.0865 | 0.45 | 50 | 0.0884 |
| 0.0878 | 0.54 | 60 | 0.0803 |
| 0.0822 | 0.63 | 70 | 0.0710 |
| 0.0763 | 0.73 | 80 | 0.0918 |
| 0.0874 | 0.82 | 90 | 0.0723 |
| 0.0807 | 0.91 | 100 | 0.0708 |
| 0.0724 | 1.0 | 110 | 0.0660 |
| 0.0644 | 1.09 | 120 | 0.0658 |
| 0.0686 | 1.18 | 130 | 0.0652 |
| 0.0626 | 1.27 | 140 | 0.0680 |
| 0.0607 | 1.36 | 150 | 0.0635 |
| 0.0645 | 1.45 | 160 | 0.0618 |
| 0.0551 | 1.54 | 170 | 0.0510 |
| 0.0474 | 1.63 | 180 | 0.0397 |
| 0.0296 | 1.72 | 190 | 0.0355 |
| 0.0381 | 1.81 | 200 | 0.0366 |
| 0.0344 | 1.9 | 210 | 0.0324 |
| 0.0304 | 1.99 | 220 | 0.0327 |
| 0.023 | 2.08 | 230 | 0.0355 |
| 0.0281 | 2.18 | 240 | 0.0334 |
| 0.0233 | 2.27 | 250 | 0.0324 |
| 0.0325 | 2.36 | 260 | 0.0368 |
| 0.0259 | 2.45 | 270 | 0.0321 |
| 0.0219 | 2.54 | 280 | 0.0325 |
| 0.0226 | 2.63 | 290 | 0.0324 |
| 0.0258 | 2.72 | 300 | 0.0321 |
| 0.0255 | 2.81 | 310 | 0.0320 |
| 0.0235 | 2.9 | 320 | 0.0322 |
| 0.027 | 2.99 | 330 | 0.0322 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.14.1
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