metadata
license: apache-2.0
tags:
- summarization
- arabic
- ar
- mt5
- Abstractive Summarization
- generated_from_trainer
datasets:
- xlsum
base_model: ahmeddbahaa/mt5-base-finetuned-persian
model-index:
- name: mt5-base-finetuned-persian-finetuned-persian-arabic
results: []
mt5-base-finetuned-persian-finetuned-persian-arabic
This model is a fine-tuned version of ahmeddbahaa/mt5-base-finetuned-persian on the xlsum dataset. It achieves the following results on the evaluation set:
- Loss: 3.3234
- Rouge-1: 22.96
- Rouge-2: 10.27
- Rouge-l: 20.95
- Gen Len: 19.0
- Bertscore: 71.59
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 |
|---|---|---|---|---|---|---|---|---|
| 4.2754 | 1.0 | 1172 | 3.5717 | 19.26 | 7.26 | 17.48 | 19.0 | 70.49 |
| 3.7388 | 2.0 | 2344 | 3.4291 | 19.71 | 7.88 | 17.94 | 19.0 | 70.64 |
| 3.541 | 3.0 | 3516 | 3.3653 | 21.18 | 8.84 | 19.35 | 19.0 | 71.05 |
| 3.4113 | 4.0 | 4688 | 3.3306 | 21.54 | 9.11 | 19.65 | 19.0 | 71.19 |
| 3.3256 | 5.0 | 5860 | 3.3234 | 21.69 | 9.22 | 19.81 | 19.0 | 71.31 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1