PHI30512HMAB1 / README.md
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---
license: mit
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
- generated_from_trainer
model-index:
- name: PHI30512HMAB1
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. -->
# PHI30512HMAB1
This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0723
## 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: 80
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 5.4839 | 0.09 | 10 | 5.4238 |
| 5.3155 | 0.18 | 20 | 4.6879 |
| 3.6592 | 0.27 | 30 | 1.9615 |
| 0.9316 | 0.36 | 40 | 0.2201 |
| 0.1779 | 0.45 | 50 | 0.1492 |
| 0.1485 | 0.54 | 60 | 0.1212 |
| 0.108 | 0.63 | 70 | 0.0889 |
| 0.0902 | 0.73 | 80 | 0.0788 |
| 0.0657 | 0.82 | 90 | 0.0730 |
| 0.0695 | 0.91 | 100 | 0.0669 |
| 0.0716 | 1.0 | 110 | 0.0673 |
| 0.0557 | 1.09 | 120 | 0.0651 |
| 0.0525 | 1.18 | 130 | 0.0684 |
| 0.0614 | 1.27 | 140 | 0.0674 |
| 0.0523 | 1.36 | 150 | 0.0651 |
| 0.0572 | 1.45 | 160 | 0.0622 |
| 0.0563 | 1.54 | 170 | 0.0620 |
| 0.0522 | 1.63 | 180 | 0.0622 |
| 0.0544 | 1.72 | 190 | 0.0619 |
| 0.0576 | 1.81 | 200 | 0.0590 |
| 0.045 | 1.9 | 210 | 0.0609 |
| 0.053 | 1.99 | 220 | 0.0611 |
| 0.0353 | 2.08 | 230 | 0.0628 |
| 0.0384 | 2.18 | 240 | 0.0687 |
| 0.0308 | 2.27 | 250 | 0.0724 |
| 0.0305 | 2.36 | 260 | 0.0746 |
| 0.0334 | 2.45 | 270 | 0.0742 |
| 0.0278 | 2.54 | 280 | 0.0742 |
| 0.0307 | 2.63 | 290 | 0.0737 |
| 0.0325 | 2.72 | 300 | 0.0732 |
| 0.037 | 2.81 | 310 | 0.0725 |
| 0.0331 | 2.9 | 320 | 0.0723 |
| 0.0295 | 2.99 | 330 | 0.0723 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0