---
license: mit
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
datasets:
- generator
base_model: microsoft/phi-2
model-index:
- name: phi-2_summarize
  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-2_summarize

This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7266

## 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: 0.0005
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 3
- training_steps: 400

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.9986        | 0.03  | 25   | 1.8320          |
| 1.8726        | 0.06  | 50   | 1.7854          |
| 1.7545        | 0.08  | 75   | 1.7727          |
| 1.8384        | 0.11  | 100  | 1.7614          |
| 1.7279        | 0.14  | 125  | 1.7561          |
| 1.7348        | 0.17  | 150  | 1.7503          |
| 1.8037        | 0.2   | 175  | 1.7442          |
| 1.7602        | 0.23  | 200  | 1.7418          |
| 1.8112        | 0.25  | 225  | 1.7372          |
| 1.7011        | 0.28  | 250  | 1.7339          |
| 1.6925        | 0.31  | 275  | 1.7312          |
| 1.6696        | 0.34  | 300  | 1.7295          |
| 1.7461        | 0.37  | 325  | 1.7275          |
| 1.6521        | 0.4   | 350  | 1.7270          |
| 1.6636        | 0.42  | 375  | 1.7267          |
| 1.7048        | 0.45  | 400  | 1.7266          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2