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---
license: mit
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
- generated_from_trainer
model-index:
- name: PHI30512HMAB2
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. -->
# PHI30512HMAB2
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: 0.0706
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 5.4852 | 0.09 | 10 | 5.4372 |
| 5.4761 | 0.18 | 20 | 5.3249 |
| 5.1807 | 0.27 | 30 | 4.6301 |
| 4.0639 | 0.36 | 40 | 3.0706 |
| 2.2191 | 0.45 | 50 | 1.1829 |
| 0.7606 | 0.54 | 60 | 0.3950 |
| 0.2685 | 0.63 | 70 | 0.1655 |
| 0.1453 | 0.73 | 80 | 0.1335 |
| 0.1187 | 0.82 | 90 | 0.1252 |
| 0.1302 | 0.91 | 100 | 0.1241 |
| 0.1114 | 1.0 | 110 | 0.1113 |
| 0.1009 | 1.09 | 120 | 0.0967 |
| 0.089 | 1.18 | 130 | 0.0971 |
| 0.1047 | 1.27 | 140 | 0.0844 |
| 0.0839 | 1.36 | 150 | 0.0811 |
| 0.0876 | 1.45 | 160 | 0.0815 |
| 0.0769 | 1.54 | 170 | 0.0813 |
| 0.081 | 1.63 | 180 | 0.0765 |
| 0.0673 | 1.72 | 190 | 0.0762 |
| 0.0789 | 1.81 | 200 | 0.0767 |
| 0.0643 | 1.9 | 210 | 0.0739 |
| 0.0715 | 1.99 | 220 | 0.0748 |
| 0.0643 | 2.08 | 230 | 0.0729 |
| 0.0626 | 2.18 | 240 | 0.0722 |
| 0.0565 | 2.27 | 250 | 0.0722 |
| 0.0594 | 2.36 | 260 | 0.0722 |
| 0.0629 | 2.45 | 270 | 0.0717 |
| 0.0594 | 2.54 | 280 | 0.0719 |
| 0.0627 | 2.63 | 290 | 0.0712 |
| 0.0582 | 2.72 | 300 | 0.0705 |
| 0.0659 | 2.81 | 310 | 0.0706 |
| 0.0603 | 2.9 | 320 | 0.0705 |
| 0.0649 | 2.99 | 330 | 0.0706 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0
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