---
base_model: microsoft/Phi-3.5-mini-instruct
datasets:
- generator
library_name: peft
license: mit
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Phi-3.5-baseline
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Phi-3.5-baseline

This model is a fine-tuned version of [microsoft/Phi-3.5-mini-instruct](https://huggingface.co/microsoft/Phi-3.5-mini-instruct) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7926

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 8
- 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: 0.03
- num_epochs: 2

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.7641        | 1.5238 | 500  | 0.7926          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.2.2+cu118
- Datasets 3.0.1
- Tokenizers 0.20.1