---
license: mit
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
- dolly
- ipex
- max series gpu
base_model: microsoft/phi-1_5
datasets:
- generator
- databricks/databricks-dolly-15k
model-index:
- name: phi-1_5-lora-tuned-sft-dolly
  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-1_5-lora-tuned-sft-dolly

This model is a fine-tuned version of [microsoft/phi-1_5](https://huggingface.co/microsoft/phi-1_5) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4000

## Model description

More information needed

## Intended uses & limitations

More information needed

## Hardware
Trained model on Intel Max 1550 GPU

## Training and evaluation data

databricks/databricks-dolly-15k

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- training_steps: 593

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.7868        | 0.8065 | 100  | 2.5808          |
| 2.547         | 1.6129 | 200  | 2.4670          |
| 2.4664        | 2.4194 | 300  | 2.4305          |
| 2.4586        | 3.2258 | 400  | 2.4108          |
| 2.4204        | 4.0323 | 500  | 2.4000          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.1.0.post0+cxx11.abi
- Datasets 2.19.1
- Tokenizers 0.19.1