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---
license: mit
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
- generated_from_trainer
model-index:
- name: Phi0503HMA3
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. -->
# Phi0503HMA3
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: 0.0755
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 4.2606 | 0.09 | 10 | 0.7405 |
| 0.359 | 0.18 | 20 | 0.2602 |
| 0.3014 | 0.27 | 30 | 0.2479 |
| 0.2182 | 0.36 | 40 | 0.1939 |
| 0.1961 | 0.45 | 50 | 0.1550 |
| 0.1655 | 0.54 | 60 | 0.0986 |
| 0.0978 | 0.63 | 70 | 0.1010 |
| 0.0847 | 0.73 | 80 | 0.0908 |
| 0.0914 | 0.82 | 90 | 0.0987 |
| 0.0854 | 0.91 | 100 | 0.0758 |
| 0.078 | 1.0 | 110 | 0.0803 |
| 0.065 | 1.09 | 120 | 0.1614 |
| 0.0712 | 1.18 | 130 | 0.0778 |
| 0.0743 | 1.27 | 140 | 0.0689 |
| 0.0586 | 1.36 | 150 | 0.0700 |
| 0.0654 | 1.45 | 160 | 0.0676 |
| 0.0609 | 1.54 | 170 | 0.0666 |
| 0.0604 | 1.63 | 180 | 0.0638 |
| 0.0511 | 1.72 | 190 | 0.0665 |
| 0.0593 | 1.81 | 200 | 0.0630 |
| 0.0528 | 1.9 | 210 | 0.0624 |
| 0.0529 | 1.99 | 220 | 0.0615 |
| 0.028 | 2.08 | 230 | 0.0727 |
| 0.026 | 2.18 | 240 | 0.0943 |
| 0.0246 | 2.27 | 250 | 0.1057 |
| 0.0215 | 2.36 | 260 | 0.0821 |
| 0.029 | 2.45 | 270 | 0.0758 |
| 0.0183 | 2.54 | 280 | 0.0778 |
| 0.0237 | 2.63 | 290 | 0.0783 |
| 0.0282 | 2.72 | 300 | 0.0765 |
| 0.0292 | 2.81 | 310 | 0.0758 |
| 0.0239 | 2.9 | 320 | 0.0755 |
| 0.0233 | 2.99 | 330 | 0.0755 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
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