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---
license: mit
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
- generated_from_trainer
model-index:
- name: PHI30512HMAB20H
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. -->
# PHI30512HMAB20H
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: 0.0752
## 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: 60
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 4.2937 | 0.09 | 10 | 0.8823 |
| 0.4617 | 0.18 | 20 | 0.2708 |
| 0.2681 | 0.27 | 30 | 2.7303 |
| 0.9935 | 0.36 | 40 | 0.2454 |
| 0.2512 | 0.45 | 50 | 0.2272 |
| 0.2279 | 0.54 | 60 | 0.2115 |
| 0.2067 | 0.63 | 70 | 0.2056 |
| 0.2419 | 0.73 | 80 | 0.1810 |
| 0.1545 | 0.82 | 90 | 0.0988 |
| 0.0955 | 0.91 | 100 | 0.0863 |
| 0.0846 | 1.0 | 110 | 0.0745 |
| 0.073 | 1.09 | 120 | 0.0728 |
| 0.0688 | 1.18 | 130 | 0.0799 |
| 0.0731 | 1.27 | 140 | 0.0723 |
| 0.0702 | 1.36 | 150 | 0.0740 |
| 0.0793 | 1.45 | 160 | 0.0680 |
| 0.0662 | 1.54 | 170 | 0.0651 |
| 0.0666 | 1.63 | 180 | 0.0636 |
| 0.0605 | 1.72 | 190 | 0.0640 |
| 0.0678 | 1.81 | 200 | 0.0666 |
| 0.0568 | 1.9 | 210 | 0.0702 |
| 0.0568 | 1.99 | 220 | 0.0660 |
| 0.0351 | 2.08 | 230 | 0.0769 |
| 0.032 | 2.18 | 240 | 0.0946 |
| 0.0288 | 2.27 | 250 | 0.0879 |
| 0.0276 | 2.36 | 260 | 0.0766 |
| 0.0316 | 2.45 | 270 | 0.0777 |
| 0.0269 | 2.54 | 280 | 0.0781 |
| 0.0265 | 2.63 | 290 | 0.0789 |
| 0.0322 | 2.72 | 300 | 0.0770 |
| 0.0362 | 2.81 | 310 | 0.0756 |
| 0.0294 | 2.9 | 320 | 0.0749 |
| 0.0277 | 2.99 | 330 | 0.0752 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0
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