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---
license: mit
tags:
- generated_from_keras_callback
model-index:
- name: bart-large-finetuned-filtered-spotify-podcast-summ
results: []
---
# bart-large-finetuned-filtered-spotify-podcast-summ
This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on on the [Spotify Podcast Dataset](https://arxiv.org/abs/2004.04270). Take a look to the [github repository](https://github.com/TheOnesThatWereAbroad/PodcastSummarization) of this project.
It achieves the following results on the evaluation set:
- Train Loss: 2.2967
- Validation Loss: 2.8316
- Epoch: 2
## Intended uses & limitations
This model is intended to be used for automatic podcast summarisation. Given the podcast transcript in input, the objective is to provide a short text summary that a user might read when deciding whether to listen to a podcast. The summary should accurately convey the content of the podcast, be human-readable, and be short enough to be quickly read on a smartphone screen.
## Training and evaluation data
We split the filtered brass set into train/dev sets of 69,336/7,705 episodes.
The test set consists of 1,027 episodes. Only 1025 have been used because two of them did not contain an episode description.
## How to use
The model can be used for the summarization as follows:
```python
from transformers import pipeline
summarizer = pipeline("summarization", model="gmurro/bart-large-finetuned-filtered-spotify-podcast-summ", tokenizer="gmurro/bart-large-finetuned-filtered-spotify-podcast-summ")
summary = summarizer(podcast_transcript, min_length=39, max_length=250)
print(summary[0]['summary_text'])
```
### Training hyperparameters
The following hyperparameters were used during training:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32
### Training results
| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 3.0440 | 2.8733 | 0 |
| 2.6085 | 2.8549 | 1 |
| 2.2967 | 2.8316 | 2 |
### Framework versions
- Transformers 4.19.4
- TensorFlow 2.9.1
- Datasets 2.3.1
- Tokenizers 0.12.1
## Authors
| Name | Surname | Email | Username |
| :-------: | :-------: | :------------------------------------: | :---------------------------------------------------: |
| Giuseppe | Boezio | `giuseppe.boezio@studio.unibo.it` | [_giuseppeboezio_](https://github.com/giuseppeboezio) |
| Simone | Montali | `simone.montali@studio.unibo.it` | [_montali_](https://github.com/montali) |
| Giuseppe | Murro | `giuseppe.murro@studio.unibo.it` | [_gmurro_](https://github.com/gmurro) |
|