|
|
--- |
|
|
license: mit |
|
|
base_model: microsoft/phi-2 |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
model-index: |
|
|
- name: V0309B2 |
|
|
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. --> |
|
|
|
|
|
# V0309B2 |
|
|
|
|
|
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: 0.0618 |
|
|
|
|
|
## 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: 4 |
|
|
- eval_batch_size: 8 |
|
|
- seed: 42 |
|
|
- gradient_accumulation_steps: 32 |
|
|
- 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: 20 |
|
|
- num_epochs: 3 |
|
|
- mixed_precision_training: Native AMP |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|
|:-------------:|:-----:|:----:|:---------------:| |
|
|
| 2.7748 | 0.09 | 10 | 2.7615 | |
|
|
| 2.5806 | 0.17 | 20 | 2.1594 | |
|
|
| 1.6958 | 0.26 | 30 | 1.0138 | |
|
|
| 0.6434 | 0.34 | 40 | 0.1676 | |
|
|
| 0.1513 | 0.43 | 50 | 0.0879 | |
|
|
| 0.1145 | 0.51 | 60 | 0.0805 | |
|
|
| 0.1 | 0.6 | 70 | 0.0744 | |
|
|
| 0.0976 | 0.68 | 80 | 0.0709 | |
|
|
| 0.0901 | 0.77 | 90 | 0.0705 | |
|
|
| 0.0869 | 0.85 | 100 | 0.0653 | |
|
|
| 0.085 | 0.94 | 110 | 0.0655 | |
|
|
| 0.0842 | 1.02 | 120 | 0.0649 | |
|
|
| 0.088 | 1.11 | 130 | 0.0686 | |
|
|
| 0.0809 | 1.19 | 140 | 0.0668 | |
|
|
| 0.0825 | 1.28 | 150 | 0.0636 | |
|
|
| 0.0783 | 1.37 | 160 | 0.0652 | |
|
|
| 0.0781 | 1.45 | 170 | 0.0663 | |
|
|
| 0.0747 | 1.54 | 180 | 0.0651 | |
|
|
| 0.0771 | 1.62 | 190 | 0.0630 | |
|
|
| 0.0739 | 1.71 | 200 | 0.0630 | |
|
|
| 0.0791 | 1.79 | 210 | 0.0624 | |
|
|
| 0.0728 | 1.88 | 220 | 0.0619 | |
|
|
| 0.0668 | 1.96 | 230 | 0.0622 | |
|
|
| 0.0757 | 2.05 | 240 | 0.0630 | |
|
|
| 0.0696 | 2.13 | 250 | 0.0626 | |
|
|
| 0.0697 | 2.22 | 260 | 0.0626 | |
|
|
| 0.0646 | 2.3 | 270 | 0.0629 | |
|
|
| 0.0737 | 2.39 | 280 | 0.0624 | |
|
|
| 0.0715 | 2.47 | 290 | 0.0621 | |
|
|
| 0.0711 | 2.56 | 300 | 0.0619 | |
|
|
| 0.0723 | 2.65 | 310 | 0.0617 | |
|
|
| 0.0675 | 2.73 | 320 | 0.0616 | |
|
|
| 0.0688 | 2.82 | 330 | 0.0615 | |
|
|
| 0.0676 | 2.9 | 340 | 0.0616 | |
|
|
| 0.0681 | 2.99 | 350 | 0.0618 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.36.0.dev0 |
|
|
- Pytorch 2.1.2+cu121 |
|
|
- Datasets 2.14.6 |
|
|
- Tokenizers 0.14.1 |
|
|
|
