license: apache-2.0
tags:
- generated_from_trainer
datasets:
- pszemraj/fleece2instructions
metrics:
- rouge
model-index:
- name: flan-t5-small-instructiongen
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: pszemraj/fleece2instructions
type: pszemraj/fleece2instructions
split: validation
metrics:
- name: Rouge1
type: rouge
value: 52.201
widget:
- text: >-
To plan a successful surprise birthday party, you'll need to start by
choosing the right venue. Consider the type of atmosphere and the size of
the area that will be suitable for the number of guests you plan to
invite. Choose the right decorations based on your brother's interests,
such as balloons in his favorite colors, banners, and streamers. Next,
decide on the food and drinks, making sure they are tasty and appropriate
for the occasion. Then decide on the other games, music, and entertainment
that will make the party memorable. Finally, involve your brother's
friends and family to help create the perfect surprise.
example_title: birthday party
- text: 1) cookies and cream 2) chocolate chip 3) mint chip 4) oreo
example_title: ice cream
- text: >-
To create a miniature diorama of a post-apocalyptic cityscape, start by
selecting a scale model of a building that fits the theme. Use a hobby
knife and glue to cut and assemble the model into a ruined or abandoned
version of itself, adding details like broken windows and graffiti. Create
a base for the diorama using foam, plaster, or other materials, and paint
it to resemble a ruined street or sidewalk. Add miniature vehicles,
debris, and figures to complete the scene, and use weathering techniques
like dry brushing and rust washes to add realism. Display the diorama in a
shadow box or other protective case to showcase your work.
example_title: Miniature diorama creation
- text: >-
To create a costume inspired by the world of cyberpunk, start by selecting
clothing that is futuristic and edgy, such as leather jackets,
neon-colored accessories, and tech-inspired patterns. Add accessories like
goggles, cybernetic implants, and LED lights to enhance the cyberpunk
vibe. Use makeup and body paint to create a futuristic look, such as
metallic skin or neon makeup. Consider adding functional elements to your
costume, such as a built-in backpack or hidden pockets for your tech
gadgets. Finally, practice your confident walk and embrace your inner
cyberpunk for a memorable and immersive costume experience.
example_title: Cyberpunk costume design
- text: >-
To create a surreal landscape using 3D software, start by creating a base
terrain with mountains, valleys, and other natural features. Use fractal
noise and displacement mapping to add texture and detail to the terrain,
and experiment with different materials like rock, grass, and water. Add
surreal elements like floating islands, giant mushrooms, or impossible
geometry to create a dreamlike atmosphere. Use lighting and color grading
to enhance the mood and tone of the scene, and render the final image at a
high resolution for maximum impact. Share your surreal landscape with the
world and inspire others to explore the possibilities of 3D art.
example_title: Surreal 3D landscape creation
- text: >-
To train for a marathon, start by setting a realistic goal and creating a
training plan. Build up your mileage gradually over time, and incorporate
cross-training and strength exercises to prevent injury and improve
endurance. Be sure to stay hydrated and properly fuel your body with
nutritious foods. Listen to your body and adjust your training as needed
to avoid overexertion or burnout. Finally, taper your training in the
weeks leading up to the race to give your body time to rest and recover
before the big day.
example_title: Marathon training
flan-t5-small-instructiongen
Instead of generating questions from text, generate instructions for LLMs!
This model is a fine-tuned version of google/flan-t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.3401
- Rouge1: 52.201
- Rouge2: 35.6154
- Rougel: 50.2334
- Rougelsum: 50.338
- Gen Len: 14.0450
Intended uses & limitations
This is just a small model/example. There is likely to be even better performance with larger models (ex pszemraj/bart-base-instructiongen) generalizes better)
Additionally, this was trained on a dataset of only instructions+outputs, with the inputs
filtered out. This means that text of 1) cookies and cream 2) chocolate chip 3) mint chip 4) oreo will not get you "Rank the following ice cream flavors: oreo, mint chip, chocolate chip, cookies and cream".
Training and evaluation data
See the linked dataset pszemraj/fleece2instructions
- it is a filtered/formatted version of tatsu-lab/alpaca
to generate instructions for arbitrary text.
- Some of the API examples are intentionally weird to demonstrate the generalizability of the model.
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 8e-05
- train_batch_size: 8
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.02
- num_epochs: 2.0
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
1.6161 | 1.0 | 181 | 1.3714 | 51.1003 | 34.5701 | 49.1277 | 49.2466 | 13.8357 |
1.539 | 2.0 | 362 | 1.3401 | 52.201 | 35.6154 | 50.2334 | 50.338 | 14.0450 |