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---
license: mit
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
- generated_from_trainer
model-index:
- name: PHI30511HMA14H
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. -->
# PHI30511HMA14H
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: 0.0823
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 2.6437 | 0.09 | 10 | 0.2765 |
| 0.1835 | 0.18 | 20 | 0.1451 |
| 0.1607 | 0.27 | 30 | 0.1438 |
| 0.139 | 0.36 | 40 | 0.1311 |
| 0.1248 | 0.45 | 50 | 0.1177 |
| 0.1233 | 0.54 | 60 | 0.1068 |
| 0.0966 | 0.63 | 70 | 0.0814 |
| 0.0851 | 0.73 | 80 | 0.0705 |
| 0.0809 | 0.82 | 90 | 0.0802 |
| 0.0744 | 0.91 | 100 | 0.0700 |
| 0.0788 | 1.0 | 110 | 0.0774 |
| 0.0466 | 1.09 | 120 | 0.0858 |
| 0.0576 | 1.18 | 130 | 0.0824 |
| 0.0586 | 1.27 | 140 | 0.0736 |
| 0.0619 | 1.36 | 150 | 0.0723 |
| 0.0588 | 1.45 | 160 | 0.0713 |
| 0.0524 | 1.54 | 170 | 0.0810 |
| 0.0569 | 1.63 | 180 | 0.0759 |
| 0.0502 | 1.72 | 190 | 0.0779 |
| 0.0569 | 1.81 | 200 | 0.0679 |
| 0.0517 | 1.9 | 210 | 0.0700 |
| 0.0466 | 1.99 | 220 | 0.0682 |
| 0.0213 | 2.08 | 230 | 0.0821 |
| 0.0166 | 2.18 | 240 | 0.1070 |
| 0.0177 | 2.27 | 250 | 0.1156 |
| 0.02 | 2.36 | 260 | 0.0961 |
| 0.0263 | 2.45 | 270 | 0.0826 |
| 0.0126 | 2.54 | 280 | 0.0851 |
| 0.0181 | 2.63 | 290 | 0.0858 |
| 0.0233 | 2.72 | 300 | 0.0839 |
| 0.0196 | 2.81 | 310 | 0.0827 |
| 0.0153 | 2.9 | 320 | 0.0823 |
| 0.0192 | 2.99 | 330 | 0.0823 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.14.1
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