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---
license: mit
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
- generated_from_trainer
model-index:
- name: PHI30512HMAB22H
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. -->
# PHI30512HMAB22H
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: 0.0375
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 4.9533 | 0.09 | 10 | 1.5870 |
| 0.7577 | 0.18 | 20 | 0.2615 |
| 0.2902 | 0.27 | 30 | 0.2473 |
| 0.2709 | 0.36 | 40 | 0.2446 |
| 0.26 | 0.45 | 50 | 0.2296 |
| 0.2324 | 0.54 | 60 | 0.2222 |
| 0.2278 | 0.63 | 70 | 0.2435 |
| 0.236 | 0.73 | 80 | 0.2284 |
| 0.1862 | 0.82 | 90 | 0.1793 |
| 0.1768 | 0.91 | 100 | 0.1645 |
| 0.1688 | 1.0 | 110 | 0.1509 |
| 0.1331 | 1.09 | 120 | 0.1000 |
| 0.0923 | 1.18 | 130 | 0.1010 |
| 0.097 | 1.27 | 140 | 0.0757 |
| 0.0803 | 1.36 | 150 | 0.0747 |
| 0.0813 | 1.45 | 160 | 0.0709 |
| 0.0747 | 1.54 | 170 | 0.0715 |
| 0.0726 | 1.63 | 180 | 0.0665 |
| 0.0678 | 1.72 | 190 | 0.0680 |
| 0.0692 | 1.81 | 200 | 0.0700 |
| 0.0607 | 1.9 | 210 | 0.0704 |
| 0.064 | 1.99 | 220 | 0.0667 |
| 0.0417 | 2.08 | 230 | 0.0758 |
| 0.0415 | 2.18 | 240 | 0.0743 |
| 0.0356 | 2.27 | 250 | 0.0644 |
| 0.0321 | 2.36 | 260 | 0.0600 |
| 0.0365 | 2.45 | 270 | 0.0490 |
| 0.0255 | 2.54 | 280 | 0.0453 |
| 0.0239 | 2.63 | 290 | 0.0437 |
| 0.0299 | 2.72 | 300 | 0.0404 |
| 0.0262 | 2.81 | 310 | 0.0394 |
| 0.0239 | 2.9 | 320 | 0.0375 |
| 0.0271 | 2.99 | 330 | 0.0375 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0
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