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---
license: mit
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
- generated_from_trainer
model-index:
- name: PHI30511HMA10H
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. -->
# PHI30511HMA10H
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: 0.0859
## 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: 100
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.9089 | 0.09 | 10 | 1.2284 |
| 0.5288 | 0.18 | 20 | 0.1720 |
| 0.1533 | 0.27 | 30 | 0.1436 |
| 0.1373 | 0.36 | 40 | 0.1243 |
| 0.1281 | 0.45 | 50 | 0.1184 |
| 0.1123 | 0.54 | 60 | 0.0945 |
| 0.0973 | 0.63 | 70 | 0.1022 |
| 0.0916 | 0.73 | 80 | 0.0787 |
| 0.0665 | 0.82 | 90 | 0.0685 |
| 0.0746 | 0.91 | 100 | 0.0688 |
| 0.0656 | 1.0 | 110 | 0.0695 |
| 0.0472 | 1.09 | 120 | 0.0709 |
| 0.0456 | 1.18 | 130 | 0.0672 |
| 0.0554 | 1.27 | 140 | 0.0644 |
| 0.046 | 1.36 | 150 | 0.0653 |
| 0.0531 | 1.45 | 160 | 0.0609 |
| 0.0486 | 1.54 | 170 | 0.0649 |
| 0.0493 | 1.63 | 180 | 0.0616 |
| 0.0464 | 1.72 | 190 | 0.0636 |
| 0.0522 | 1.81 | 200 | 0.0612 |
| 0.0423 | 1.9 | 210 | 0.0606 |
| 0.0457 | 1.99 | 220 | 0.0606 |
| 0.0224 | 2.08 | 230 | 0.0676 |
| 0.022 | 2.18 | 240 | 0.0788 |
| 0.016 | 2.27 | 250 | 0.0873 |
| 0.0137 | 2.36 | 260 | 0.0910 |
| 0.0204 | 2.45 | 270 | 0.0903 |
| 0.0146 | 2.54 | 280 | 0.0899 |
| 0.0172 | 2.63 | 290 | 0.0890 |
| 0.0206 | 2.72 | 300 | 0.0870 |
| 0.02 | 2.81 | 310 | 0.0863 |
| 0.0186 | 2.9 | 320 | 0.0860 |
| 0.0175 | 2.99 | 330 | 0.0859 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.14.1
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