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---
license: mit
library_name: peft
tags:
- generated_from_trainer
base_model: microsoft/Phi-3-mini-128k-instruct
model-index:
- name: working
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. -->
# working
This model is a fine-tuned version of [microsoft/Phi-3-mini-128k-instruct](https://huggingface.co/microsoft/Phi-3-mini-128k-instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6374
## 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: 0.0002
- train_batch_size: 6
- eval_batch_size: 6
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.6546 | 0.92 | 6 | 1.7189 |
| 1.2076 | 2.0 | 13 | 0.8973 |
| 0.7157 | 2.92 | 19 | 0.5511 |
| 0.4138 | 4.0 | 26 | 0.4499 |
| 0.4018 | 4.92 | 32 | 0.4044 |
| 0.3034 | 6.0 | 39 | 0.3793 |
| 0.3186 | 6.92 | 45 | 0.3645 |
| 0.2451 | 8.0 | 52 | 0.3590 |
| 0.2556 | 8.92 | 58 | 0.3660 |
| 0.1937 | 10.0 | 65 | 0.3825 |
| 0.1993 | 10.92 | 71 | 0.3782 |
| 0.1511 | 12.0 | 78 | 0.4275 |
| 0.1487 | 12.92 | 84 | 0.4234 |
| 0.1098 | 14.0 | 91 | 0.4876 |
| 0.1121 | 14.92 | 97 | 0.4675 |
| 0.0846 | 16.0 | 104 | 0.5187 |
| 0.0869 | 16.92 | 110 | 0.5365 |
| 0.0677 | 18.0 | 117 | 0.5372 |
| 0.0729 | 18.92 | 123 | 0.5639 |
| 0.0587 | 20.0 | 130 | 0.5773 |
| 0.0623 | 20.92 | 136 | 0.6006 |
| 0.0524 | 22.0 | 143 | 0.6098 |
| 0.0599 | 22.92 | 149 | 0.6101 |
| 0.0495 | 24.0 | 156 | 0.6204 |
| 0.0571 | 24.92 | 162 | 0.6297 |
| 0.0475 | 26.0 | 169 | 0.6353 |
| 0.0551 | 26.92 | 175 | 0.6374 |
| 0.0455 | 27.69 | 180 | 0.6374 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2 |