---
license: cc-by-nc-4.0
base_model: MBZUAI/LaMini-Flan-T5-248M
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: Lamini-Prompt-Enchance
  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. -->

# Usage

```python
from transformers import pipeline     

# load model and tokenizer from huggingface hub with pipeline
enhancer = pipeline("summarization", model="gokaygokay/Lamini-Prompt-Enchance", device=0)

prompt = "A blue-tinted bedroom scene, surreal and serene, with a mysterious reflected interior."
prefix = "Enhance the description: "
# enhance prompt
res = enhancer(prefix + prompt)

print(res[0]['summary_text'])

# A surreal and serene bedroom scene with a mysterious mirrored interior, 
# awash in blue and green hues.
# The room is adorned with intricate patterns and a mirrored wall, 
# creating a sense of mystery and tranquility.
```

# Lamini-Prompt-Enchance

This model is a fine-tuned version of [MBZUAI/LaMini-Flan-T5-248M](https://huggingface.co./MBZUAI/LaMini-Flan-T5-248M) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0195
- Rouge1: 31.5042
- Rouge2: 13.2633
- Rougel: 26.4176
- Rougelsum: 28.4846
- Gen Len: 19.0

## 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: 5e-05
- train_batch_size: 24
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log        | 1.0   | 115  | 2.1369          | 31.6298 | 13.2671 | 26.4264 | 28.5472   | 19.0    |
| No log        | 2.0   | 230  | 2.0733          | 31.4969 | 13.2677 | 26.5009 | 28.4785   | 19.0    |
| No log        | 3.0   | 345  | 2.0405          | 31.4735 | 13.01   | 26.1931 | 28.3299   | 19.0    |
| No log        | 4.0   | 460  | 2.0250          | 31.4761 | 13.2096 | 26.3479 | 28.3059   | 19.0    |
| 2.2448        | 5.0   | 575  | 2.0195          | 31.5042 | 13.2633 | 26.4176 | 28.4846   | 19.0    |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1