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---
base_model: microsoft/Phi-3-mini-4k-instruct
library_name: peft
license: mit
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: phi-3-mini-LoRA-MEDQA-Extended-V2
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. -->
# phi-3-mini-LoRA-MEDQA-Extended-V2
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: 0.6515
## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.7812 | 0.2205 | 100 | 0.6948 |
| 0.6796 | 0.4410 | 200 | 0.6695 |
| 0.6687 | 0.6615 | 300 | 0.6632 |
| 0.662 | 0.8820 | 400 | 0.6599 |
| 0.6603 | 1.1025 | 500 | 0.6579 |
| 0.6587 | 1.3230 | 600 | 0.6568 |
| 0.6539 | 1.5436 | 700 | 0.6553 |
| 0.6552 | 1.7641 | 800 | 0.6540 |
| 0.6542 | 1.9846 | 900 | 0.6537 |
| 0.6501 | 2.2051 | 1000 | 0.6526 |
| 0.6523 | 2.4256 | 1100 | 0.6521 |
| 0.6527 | 2.6461 | 1200 | 0.6517 |
| 0.6502 | 2.8666 | 1300 | 0.6515 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.43.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |