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---
tags:
- generated_from_trainer
datasets:
- xlsum
metrics:
- rouge
model-index:
- name: mT5-finetuned-xlsum
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: xlsum
type: xlsum
config: arabic
split: validation
args: arabic
metrics:
- name: Rouge1
type: rouge
value: 0.1179
---
<!-- 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-finetuned-xlsum
This model is a fine-tuned version of [csebuetnlp/mT5_m2o_arabic_crossSum](https://huggingface.co/csebuetnlp/mT5_m2o_arabic_crossSum) on the xlsum dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6752
- Rouge1: 0.1179
- Rouge2: 0.0231
- Rougel: 0.118
- Rougelsum: 0.1178
- Gen Len: 47.6818
## 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
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 0.8728 | 1.0 | 9380 | 0.6752 | 0.1179 | 0.0231 | 0.118 | 0.1178 | 47.6818 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.13.1
- Tokenizers 0.13.3
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