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---
license: mit
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
- generated_from_trainer
model-index:
- name: PHI30515HMA2H
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. -->
# PHI30515HMA2H
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: 0.0706
## 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 7.1779 | 0.09 | 10 | 2.1285 |
| 1.3773 | 0.18 | 20 | 0.3216 |
| 0.3479 | 0.27 | 30 | 0.2281 |
| 0.9413 | 0.36 | 40 | 0.3169 |
| 0.2771 | 0.45 | 50 | 0.1485 |
| 0.332 | 0.54 | 60 | 0.1472 |
| 0.2391 | 0.63 | 70 | 0.1359 |
| 0.1792 | 0.73 | 80 | 0.1238 |
| 0.1223 | 0.82 | 90 | 0.1178 |
| 0.1279 | 0.91 | 100 | 0.0860 |
| 0.109 | 1.0 | 110 | 0.0776 |
| 0.0986 | 1.09 | 120 | 0.0769 |
| 0.0989 | 1.18 | 130 | 0.0739 |
| 0.117 | 1.27 | 140 | 0.0712 |
| 0.1134 | 1.36 | 150 | 0.0686 |
| 0.0768 | 1.45 | 160 | 0.0661 |
| 0.0932 | 1.54 | 170 | 0.1176 |
| 0.0865 | 1.63 | 180 | 0.0759 |
| 0.0974 | 1.72 | 190 | 0.0680 |
| 0.0831 | 1.81 | 200 | 0.0715 |
| 0.0732 | 1.9 | 210 | 0.1637 |
| 0.0756 | 1.99 | 220 | 0.0676 |
| 0.0457 | 2.08 | 230 | 0.0696 |
| 0.0551 | 2.18 | 240 | 0.0779 |
| 0.0391 | 2.27 | 250 | 0.0772 |
| 0.0401 | 2.36 | 260 | 0.0749 |
| 0.0448 | 2.45 | 270 | 0.0707 |
| 0.0422 | 2.54 | 280 | 0.0731 |
| 0.037 | 2.63 | 290 | 0.0732 |
| 0.039 | 2.72 | 300 | 0.0727 |
| 0.0465 | 2.81 | 310 | 0.0718 |
| 0.051 | 2.9 | 320 | 0.0707 |
| 0.0416 | 2.99 | 330 | 0.0706 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0
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