|
--- |
|
license: apache-2.0 |
|
tags: |
|
- summarization |
|
- arabic |
|
- ar |
|
- mt5 |
|
- Abstractive Summarization |
|
- generated_from_trainer |
|
datasets: |
|
- xlsum |
|
base_model: google/mt5-base |
|
model-index: |
|
- name: mt5-base-arabic |
|
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. --> |
|
|
|
# mt5-base-arabic |
|
|
|
This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on arabic subset on the xlsum dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 3.2742 |
|
- Rouge-1: 22.86 |
|
- Rouge-2: 10.31 |
|
- Rouge-l: 20.85 |
|
- Gen Len: 19.0 |
|
- Bertscore: 71.52 |
|
|
|
## 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: 0.0005 |
|
- train_batch_size: 4 |
|
- eval_batch_size: 4 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 8 |
|
- total_train_batch_size: 32 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 5 |
|
- label_smoothing_factor: 0.1 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge-1 | Rouge-2 | Rouge-l | Gen Len | Bertscore | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:| |
|
| 4.2331 | 1.0 | 1172 | 3.5051 | 18.54 | 6.63 | 16.77 | 19.0 | 70.28 | |
|
| 3.7075 | 2.0 | 2344 | 3.3737 | 19.99 | 7.94 | 18.19 | 19.0 | 70.79 | |
|
| 3.5132 | 3.0 | 3516 | 3.3171 | 20.76 | 8.57 | 18.96 | 19.0 | 70.95 | |
|
| 3.3859 | 4.0 | 4688 | 3.2811 | 21.49 | 8.99 | 19.51 | 19.0 | 71.19 | |
|
| 3.3012 | 5.0 | 5860 | 3.2742 | 21.79 | 9.18 | 19.77 | 19.0 | 71.25 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.18.0 |
|
- Pytorch 1.11.0+cu113 |
|
- Datasets 2.1.0 |
|
- Tokenizers 0.12.1 |
|
|
