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---
base_model: microsoft/Phi-3-mini-4k-instruct
library_name: peft
license: mit
tags:
- generated_from_trainer
model-index:
- name: phi3-mini-4k-adapter_3
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-mini-4k-adapter_3
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: 0.1650
## 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: cosine
- lr_scheduler_warmup_ratio: 0.05
- training_steps: 200
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 9.3301 | 0.9091 | 10 | 7.3651 |
| 0.24 | 1.8182 | 20 | 0.2340 |
| 0.1173 | 2.7273 | 30 | 0.1572 |
| 0.0836 | 3.6364 | 40 | 0.1480 |
| 0.0681 | 4.5455 | 50 | 0.1554 |
| 0.0607 | 5.4545 | 60 | 0.1496 |
| 0.0555 | 6.3636 | 70 | 0.1650 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.43.1
- Pytorch 2.4.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1 |