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license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0309P4
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. -->
# V0309P4
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: 0.0689
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 2.1886 | 0.09 | 10 | 0.9747 |
| 0.3651 | 0.17 | 20 | 0.0977 |
| 0.1129 | 0.26 | 30 | 0.0765 |
| 0.0955 | 0.34 | 40 | 0.0707 |
| 0.0894 | 0.43 | 50 | 0.0684 |
| 0.083 | 0.51 | 60 | 0.0679 |
| 0.0762 | 0.6 | 70 | 0.0688 |
| 0.0807 | 0.68 | 80 | 0.0672 |
| 0.0699 | 0.77 | 90 | 0.0735 |
| 0.0699 | 0.85 | 100 | 0.0735 |
| 0.0757 | 0.94 | 110 | 0.0663 |
| 0.0726 | 1.02 | 120 | 0.0632 |
| 0.0641 | 1.11 | 130 | 0.0692 |
| 0.0627 | 1.19 | 140 | 0.0625 |
| 0.0579 | 1.28 | 150 | 0.0625 |
| 0.0579 | 1.37 | 160 | 0.0682 |
| 0.0564 | 1.45 | 170 | 0.0642 |
| 0.0544 | 1.54 | 180 | 0.0651 |
| 0.0565 | 1.62 | 190 | 0.0623 |
| 0.057 | 1.71 | 200 | 0.0605 |
| 0.0589 | 1.79 | 210 | 0.0602 |
| 0.0538 | 1.88 | 220 | 0.0659 |
| 0.0528 | 1.96 | 230 | 0.0623 |
| 0.0482 | 2.05 | 240 | 0.0640 |
| 0.0396 | 2.13 | 250 | 0.0693 |
| 0.0398 | 2.22 | 260 | 0.0753 |
| 0.0372 | 2.3 | 270 | 0.0771 |
| 0.0463 | 2.39 | 280 | 0.0707 |
| 0.0447 | 2.47 | 290 | 0.0676 |
| 0.0429 | 2.56 | 300 | 0.0672 |
| 0.0454 | 2.65 | 310 | 0.0670 |
| 0.0377 | 2.73 | 320 | 0.0678 |
| 0.0387 | 2.82 | 330 | 0.0690 |
| 0.0394 | 2.9 | 340 | 0.0690 |
| 0.0414 | 2.99 | 350 | 0.0689 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
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