metadata
base_model: UBC-NLP/AraT5v2-base-1024
tags:
- summarization
- Arat5v2
- abstractive summarization
- ar
- wikilingua
- generated_from_trainer
datasets:
- wiki_lingua
model-index:
- name: AraT5v2-base-1024-finetuned-ar-wikilingua
results: []
AraT5v2-base-1024-finetuned-ar-wikilingua
This model is a fine-tuned version of UBC-NLP/AraT5v2-base-1024 on the wiki_lingua dataset. It achieves the following results on the evaluation set:
- Loss: 4.1591
- Rouge-1: 26.54
- Rouge-2: 10.4
- Rouge-l: 23.72
- Gen Len: 18.19
- Bertscore: 72.52
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- num_epochs: 8
- label_smoothing_factor: 0.1
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge-1 | Rouge-2 | Rouge-l | Gen Len | Bertscore |
|---|---|---|---|---|---|---|---|---|
| 5.2884 | 1.0 | 4998 | 4.4307 | 23.0 | 8.16 | 20.56 | 17.66 | 70.77 |
| 4.6798 | 2.0 | 9996 | 4.2972 | 24.48 | 8.95 | 21.86 | 17.57 | 71.56 |
| 4.4355 | 3.0 | 14994 | 4.2313 | 24.85 | 9.17 | 22.23 | 17.68 | 71.7 |
| 4.2772 | 4.0 | 19992 | 4.1972 | 25.41 | 9.5 | 22.65 | 17.63 | 72.08 |
| 4.1551 | 5.0 | 24990 | 4.1724 | 25.43 | 9.44 | 22.58 | 17.68 | 72.08 |
| 4.0604 | 6.0 | 29988 | 4.1626 | 25.44 | 9.56 | 22.67 | 17.52 | 72.19 |
| 3.989 | 7.0 | 34986 | 4.1616 | 25.71 | 9.68 | 22.91 | 17.71 | 72.29 |
| 3.9467 | 8.0 | 39984 | 4.1591 | 25.81 | 9.81 | 23.03 | 17.67 | 72.33 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3