---
license: apache-2.0
base_model: facebook/bart-large
tags:
- generated_from_trainer
model-index:
- name: bart_keywords
  results: []
pipeline_tag: text2text-generation
datasets:
- sunhaozhepy/ag_news_keywords
language:
- en
---

<!-- 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. -->

# Model description

This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on a dataset in the hub called [sunhaozhepy/ag_news_keywords_embeddings](https://huggingface.co/datasets/sunhaozhepy/ag_news_keywords_embeddings) to extract main keywords from text.
It achieves the following results on the evaluation set:
- Loss: 0.6179

## Intended use

```
from transformers import pipeline

pipe = pipeline('summarization', model='bart_keywords_model')
print(pipe("Aria Opera GPT version - All the browsers come with their own version of AI. So I gave it a try and ask it with LLM it was using. First if all it didn't understand the question. Then I explained and asked which version. I got the usual answer about a language model that is not aware of it's own model I find that curious, but also not transparent. My laptop, software all state their versions and critical information. But something that can easily fool a lot of people doesn't. What I also wonder if the general public will be stuck to ChatGPT 3.5 for ever while better models are behind expensive paywalls."))

```

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.7701        | 0.57  | 500  | 0.7390          |
| 0.5804        | 1.14  | 1000 | 0.7056          |
| 0.5395        | 1.71  | 1500 | 0.6811          |
| 0.4036        | 2.28  | 2000 | 0.6504          |
| 0.3763        | 2.85  | 2500 | 0.6179          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0