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datasets: readerbench/AlephNews
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Model card for RoSummary-base
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language:
- ro
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# RoSummary
This is a version of the RoGPT2 model trained on the [AlephNews](https://huggingface.co/datasets/readerbench/AlephNews) dataset for the summarization task. There are 3 trained versions, they are available on the HuggingFace Hub:
* [base](https://huggingface.co/readerbench/RoSummary-base)
* [medium](https://huggingface.co/readerbench/RoSummary-medium)
* [large](https://huggingface.co/readerbench/RoSummary-large)
## Evaluation on [AlephNews](https://huggingface.co/datasets/readerbench/AlephNews)
| Model | Decode Method | | BERTScore | | | ROUGE | |
|:------:|:--------------:|:---------:|:---------:|:--------:|:--------:|:--------:|:--------:|
| | | Precision | Recall | F1-Score | ROUGE-1 | ROUGE-2 | ROUGE-L |
| | Greedy | 0.7335 | 0.7399 | 0.7358 | 0.3360 | 0.1862 | 0.3333 |
| Base | Beam Search | 0.7354 | 0.7468 | 0.7404 | 0.3480 | 0.1991 | 0.3416 |
| | Top-p Sampling | 0.7296 | 0.7299 | 0.7292 | 0.3058 | 0.1452 | 0.2951 |
| | Greedy | 0.7378 | 0.7401 | 0.7380 | 0.3422 | 0.1922 | 0.3394 |
| Medium | Beam Search | 0.7390 | **0.7493**|**0.7434**|**0.3546**|**0.2061**|**0.3467**|
| | Top-p Sampling | 0.7315 | 0.7285 | 0.7294 | 0.3042 | 0.1400 | 0.2921 |
| | Greedy | 0.7376 | 0.7424 | 0.7391 | 0.3414 | 0.1895 | 0.3355 |
| Large | Beam Search | **0.7394**| 0.7470 | 0.7424 | 0.3492 | 0.1995 | 0.3384 |
| | Top-p Sampling | 0.7311 | 0.7301 | 0.7299 | 0.3051 | 0.1418 | 0.2931 |
## Acknowledgments
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Research supported with [Cloud TPUs](https://cloud.google.com/tpu/) from Google's [TensorFlow Research Cloud (TFRC)](https://www.tensorflow.org/tfrc)
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