---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- pszemraj/fleece2instructions
metrics:
- rouge
model-index:
- name: bart-base-fleece2instructions-r1
  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: 61.7209
widget:
- text: "To be fair, you have to have a very high IQ to understand Rick and Morty. The humour is extremely subtle, and without a solid grasp of theoretical physics most of the jokes will go over a typical viewer's head. There's also Rick's nihilistic outlook, which is deftly woven into his characterisation- his personal philosophy draws heavily from Narodnaya Volya literature, for instance. The fans understand this stuff; they have the intellectual capacity to truly appreciate the depths of these jokes, to realise that they're not just funny- they say something deep about LIFE. As a consequence people who dislike Rick & Morty truly ARE idiots- of course they wouldn't appreciate, for instance, the humour in Rick's existential catchphrase \"Wubba Lubba Dub Dub,\" which itself is a cryptic reference to Turgenev's Russian epic Fathers and Sons. I'm smirking right now just imagining one of those addlepated simpletons scratching their heads in confusion as Dan Harmon's genius wit unfolds itself on their television screens. What fools.. how I pity them. 😂 And yes, by the way, i DO have a Rick & Morty tattoo. And no, you cannot see it. It's for the ladies' eyes only- and even then they have to demonstrate that they're within 5 IQ points of my own (preferably lower) beforehand. Nothin personnel kid 😎"
  example_title: "Sentiment analysis"
- text: "Barack Obama nominated Hilary Clinton as his secretary of state on Monday. He chose her because she had ..."
  example_title: "Coreference resolution"
- text: "On a shelf, there are five books: a gray book, a red book, a purple book, a blue book, and a black book. The gray book is to the left of the red book. The purple book is to the right of the blue book. The black book is to the right of the gray book. What is the order of the books from left to right?"
  example_title: "Logic puzzles"
- text: "The two men running to become New York City's next mayor will face off in their first debate Wednesday night. Eric Adams and Andrew Yang, the leading contenders in the crowded Democratic primary, are scheduled to appear together in a live televised forum. The event, which is being hosted by WABC-TV, will be moderated by Eyewitness News anchor Bill Ritter and political reporter Dave Evans. Adams, the Brooklyn borough president, and Yang, the entrepreneur and former presidential candidate, have been vying for the top spot in recent polls, with the election just weeks away."
  example_title: "Reading comprehension"
- text: "A customer orders a pizza with pepperoni, mushrooms, and extra cheese. The pizza maker prepares the pizza by placing a layer of tomato sauce on the crust, followed by the pepperoni, mushrooms, and cheese. The pizza is then baked in the oven until the cheese is melted and bubbly. When the pizza is ready, it is sliced into 8 equal pieces and served to the customer."
  example_title: "Sequence to sequence"
- text: "Scientists at the Massachusetts Institute of Technology have developed a new way of detecting brain activity using lasers. The technique involves shining a laser onto the scalp and detecting the scattered light that bounces back from the brain. This allows researchers to measure changes in blood flow and oxygen levels, which are indicators of brain activity. The new method is non-invasive and could be used to study a wide range of neurological conditions, including Alzheimer's disease, stroke, and others"
---


# bart-base-instructiongen

This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the pszemraj/fleece2instructions dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0034
- Rouge1: 61.7209
- Rouge2: 45.0116
- Rougel: 59.8188
- Rougelsum: 59.8931
- Gen Len: 14.3179

## Model description

More information needed

## Intended uses & limitations

More information needed

## 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.


## 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: 8
- 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: 0.02
- num_epochs: 2.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.2723        | 1.0   | 362  | 1.0325          | 61.6206 | 45.1199 | 59.6467 | 59.7534   | 14.0443 |
| 1.0157        | 2.0   | 724  | 1.0034          | 62.4433 | 46.0114 | 60.5355 | 60.6392   | 14.1807 |