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---
license: mit
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
- generated_from_trainer
model-index:
- name: Phi0503HMA4
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. -->
# Phi0503HMA4
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: 0.0958
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 4.3203 | 0.09 | 10 | 0.8287 |
| 0.439 | 0.18 | 20 | 0.2584 |
| 0.2853 | 0.27 | 30 | 0.2324 |
| 0.3519 | 0.36 | 40 | 0.2819 |
| 0.2642 | 0.45 | 50 | 1.2134 |
| 3.7539 | 0.54 | 60 | 4.0368 |
| 2.718 | 0.63 | 70 | 1.9987 |
| 1.3059 | 0.73 | 80 | 0.5453 |
| 0.534 | 0.82 | 90 | 0.4644 |
| 0.3535 | 0.91 | 100 | 0.2428 |
| 0.2618 | 1.0 | 110 | 0.2259 |
| 0.2222 | 1.09 | 120 | 0.2072 |
| 0.1939 | 1.18 | 130 | 0.1850 |
| 0.2268 | 1.27 | 140 | 0.1876 |
| 0.1966 | 1.36 | 150 | 0.1927 |
| 0.1942 | 1.45 | 160 | 0.1838 |
| 0.1937 | 1.54 | 170 | 0.1900 |
| 0.1808 | 1.63 | 180 | 0.1781 |
| 0.1785 | 1.72 | 190 | 0.1795 |
| 0.1737 | 1.81 | 200 | 0.1694 |
| 0.176 | 1.9 | 210 | 0.1708 |
| 0.1648 | 1.99 | 220 | 0.1751 |
| 0.1702 | 2.08 | 230 | 0.1576 |
| 0.1576 | 2.18 | 240 | 0.1524 |
| 0.1477 | 2.27 | 250 | 0.1389 |
| 0.1333 | 2.36 | 260 | 0.1172 |
| 0.1267 | 2.45 | 270 | 0.1126 |
| 0.1128 | 2.54 | 280 | 0.1016 |
| 0.1112 | 2.63 | 290 | 0.0995 |
| 0.1032 | 2.72 | 300 | 0.0976 |
| 0.1001 | 2.81 | 310 | 0.0971 |
| 0.0996 | 2.9 | 320 | 0.0957 |
| 0.0968 | 2.99 | 330 | 0.0958 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
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