| datasets: readerbench/AlephNews | |
| Model card for RoSummary-base | |
| --- | |
| language: | |
| - ro | |
| --- | |
| # 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 | |
| --- | |
| Research supported with [Cloud TPUs](https://cloud.google.com/tpu/) from Google's [TensorFlow Research Cloud (TFRC)](https://www.tensorflow.org/tfrc) | |