| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: moussaKam/AraBART |
| tags: |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: AraBART-traffics-summarization |
| results: [] |
| --- |
| |
| <!-- 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. --> |
|
|
| # AraBART-traffics-summarization |
|
|
| This model is a fine-tuned version of [moussaKam/AraBART](https://huggingface.co/moussaKam/AraBART) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.5301 |
| - Rouge1: 0.8041 |
| - Rouge2: 0.7628 |
| - Rougel: 0.8027 |
| - Rougelsum: 0.8035 |
|
|
| ## 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: 32 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.05 |
| - num_epochs: 5 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:| |
| | No log | 1.0 | 326 | 0.5848 | 0.7780 | 0.7365 | 0.7773 | 0.7779 | |
| | 1.0582 | 2.0 | 652 | 0.5345 | 0.7951 | 0.7535 | 0.7942 | 0.7947 | |
| | 1.0582 | 3.0 | 978 | 0.5332 | 0.7964 | 0.7536 | 0.7955 | 0.7960 | |
| | 0.5142 | 4.0 | 1304 | 0.5217 | 0.8016 | 0.7579 | 0.8009 | 0.8015 | |
| | 0.3681 | 5.0 | 1630 | 0.5301 | 0.8041 | 0.7628 | 0.8027 | 0.8035 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.44.2 |
| - Pytorch 2.1.1+cu121 |
| - Datasets 2.21.0 |
| - Tokenizers 0.19.1 |
| |
