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---
base_model: microsoft/Phi-3.5-mini-instruct
library_name: peft
license: mit
tags:
- generated_from_trainer
model-index:
- name: phi3.5-mini-adapter_v1
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. -->
# phi3.5-mini-adapter_v1
This model is a fine-tuned version of [microsoft/Phi-3.5-mini-instruct](https://huggingface.co/microsoft/Phi-3.5-mini-instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0998
## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 14.2062 | 0.6061 | 10 | 13.2015 |
| 5.0286 | 1.2121 | 20 | 3.9207 |
| 0.248 | 1.8182 | 30 | 0.2396 |
| 0.1801 | 2.4242 | 40 | 0.1860 |
| 0.1496 | 3.0303 | 50 | 0.1639 |
| 0.212 | 3.6364 | 60 | 0.1333 |
| 0.0822 | 4.2424 | 70 | 0.1134 |
| 0.07 | 4.8485 | 80 | 0.1061 |
| 0.0871 | 5.4545 | 90 | 0.1178 |
| 0.0645 | 6.0606 | 100 | 0.1017 |
| 0.0558 | 6.6667 | 110 | 0.0998 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.43.1
- Pytorch 2.4.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1 |