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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-large-fleece2instructions-r1
results: []
widget:
- text: >-
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: >-
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: >-
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: >-
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: >-
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
---
<!-- 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. -->
# bart-large-fleece2instructions-r1
This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0436
- Rouge1: 64.4538
- Rouge2: 47.8829
- Rougel: 62.5085
- Rougelsum: 62.6165
- Gen Len: 14.4780
## 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: 6e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 2.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.0379 | 1.0 | 362 | 1.0932 | 62.4953 | 46.0277 | 60.6748 | 60.7667 | 14.5614 |
| 0.925 | 2.0 | 724 | 1.0436 | 64.4538 | 47.8829 | 62.5085 | 62.6165 | 14.4780 |
### Framework versions
- Transformers 4.25.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.0
- Tokenizers 0.13.2
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