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---
license: mit
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
- generated_from_trainer
model-index:
- name: PHI30512HMAB4H
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. -->
# PHI30512HMAB4H
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: 0.0863
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 4.7212 | 0.09 | 10 | 1.7615 |
| 0.8243 | 0.18 | 20 | 0.3615 |
| 0.3349 | 0.27 | 30 | 0.2864 |
| 0.3202 | 0.36 | 40 | 0.2662 |
| 0.6542 | 0.45 | 50 | 0.2339 |
| 0.2334 | 0.54 | 60 | 0.2159 |
| 0.4715 | 0.63 | 70 | 0.7325 |
| 1.1442 | 0.73 | 80 | 0.9402 |
| 2.8468 | 0.82 | 90 | 4.9739 |
| 2.3962 | 0.91 | 100 | 0.9736 |
| 0.6771 | 1.0 | 110 | 0.4388 |
| 0.4592 | 1.09 | 120 | 0.3687 |
| 0.3319 | 1.18 | 130 | 0.2208 |
| 0.248 | 1.27 | 140 | 0.1911 |
| 0.2015 | 1.36 | 150 | 0.1909 |
| 0.2016 | 1.45 | 160 | 0.2083 |
| 0.2028 | 1.54 | 170 | 0.1676 |
| 0.1686 | 1.63 | 180 | 0.1661 |
| 0.1546 | 1.72 | 190 | 0.1469 |
| 0.1708 | 1.81 | 200 | 0.1622 |
| 0.1494 | 1.9 | 210 | 0.1380 |
| 0.1412 | 1.99 | 220 | 0.1445 |
| 0.1389 | 2.08 | 230 | 0.1363 |
| 0.1386 | 2.18 | 240 | 0.1266 |
| 0.1307 | 2.27 | 250 | 0.1289 |
| 0.1261 | 2.36 | 260 | 0.1213 |
| 0.123 | 2.45 | 270 | 0.1142 |
| 0.1098 | 2.54 | 280 | 0.1067 |
| 0.1063 | 2.63 | 290 | 0.1014 |
| 0.0987 | 2.72 | 300 | 0.0947 |
| 0.0955 | 2.81 | 310 | 0.0904 |
| 0.0946 | 2.9 | 320 | 0.0882 |
| 0.0854 | 2.99 | 330 | 0.0863 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0
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