metadata
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- xlsum
metrics:
- rouge
model-index:
- name: mt5-finetuned-en-ar
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: xlsum
type: xlsum
args: arabic
metrics:
- name: Rouge1
type: rouge
value: 0.2824
mt5-finetuned-en-ar
This model is a fine-tuned version of ahmeddbahaa/mt5-small-finetuned-mt5-en on the xlsum dataset. It achieves the following results on the evaluation set:
- Loss: 2.2314
- Rouge1: 0.2824
- Rouge2: 0.0
- Rougel: 0.2902
- Rougelsum: 0.298
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 3.1685 | 1.0 | 4130 | 2.4262 | 0.0941 | 0.0235 | 0.1098 | 0.1098 |
| 2.686 | 2.0 | 8260 | 2.2853 | 0.2824 | 0.0 | 0.298 | 0.298 |
| 2.481 | 3.0 | 12390 | 2.2314 | 0.2824 | 0.0 | 0.2902 | 0.298 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6