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---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0422MADP4C
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. -->
# V0422MADP4C
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: 0.0645
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 5.2111 | 0.09 | 10 | 1.5167 |
| 2.2548 | 0.18 | 20 | 0.1595 |
| 0.4128 | 0.27 | 30 | 0.1403 |
| 0.169 | 0.36 | 40 | 0.1317 |
| 0.1338 | 0.45 | 50 | 0.1031 |
| 0.1151 | 0.54 | 60 | 0.0947 |
| 0.0959 | 0.63 | 70 | 0.0844 |
| 0.0888 | 0.73 | 80 | 0.0796 |
| 0.0899 | 0.82 | 90 | 0.0807 |
| 0.0912 | 0.91 | 100 | 0.0758 |
| 0.0926 | 1.0 | 110 | 0.0711 |
| 0.0795 | 1.09 | 120 | 0.0754 |
| 0.0992 | 1.18 | 130 | 0.0936 |
| 0.0917 | 1.27 | 140 | 0.0777 |
| 0.2413 | 1.36 | 150 | 0.1380 |
| 0.1347 | 1.45 | 160 | 0.0987 |
| 0.1056 | 1.54 | 170 | 0.0780 |
| 0.0903 | 1.63 | 180 | 0.0736 |
| 0.0827 | 1.72 | 190 | 0.0713 |
| 0.0864 | 1.81 | 200 | 0.0839 |
| 0.0796 | 1.9 | 210 | 0.0808 |
| 0.0782 | 1.99 | 220 | 0.0747 |
| 0.0716 | 2.08 | 230 | 0.0691 |
| 0.0689 | 2.18 | 240 | 0.0679 |
| 0.0669 | 2.27 | 250 | 0.0660 |
| 0.068 | 2.36 | 260 | 0.0649 |
| 0.0658 | 2.45 | 270 | 0.0655 |
| 0.0639 | 2.54 | 280 | 0.0654 |
| 0.0602 | 2.63 | 290 | 0.0647 |
| 0.0619 | 2.72 | 300 | 0.0647 |
| 0.0687 | 2.81 | 310 | 0.0648 |
| 0.0624 | 2.9 | 320 | 0.0645 |
| 0.0711 | 2.99 | 330 | 0.0645 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.14.1
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