metadata

license: apache-2.0
tags:
  - summarization
  - generated_from_trainer
datasets:
  - wiki_lingua
metrics:
  - rouge
model-index:
  - name: wiki_lingua-ar-8-8-5.6e-05-mt5-small-finetuned
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: wiki_lingua
          type: wiki_lingua
          config: ar
          split: test
          args: ar
        metrics:
          - name: Rouge1
            type: rouge
            value: 0.5417

wiki_lingua-ar-8-8-5.6e-05-mt5-small-finetuned

This model is a fine-tuned version of google/mt5-small on the wiki_lingua dataset. It achieves the following results on the evaluation set:

Loss: 2.3401
Rouge1: 0.5417
Rouge2: 0.0921
Rougel: 0.5445
Rougelsum: 0.5404

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: 5.6e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
3.851	1.0	2499	2.5949	0.4653	0.1378	0.4684	0.4631
3.0409	2.0	4998	2.4790	0.4825	0.1156	0.4834	0.4798
2.8824	3.0	7497	2.4273	0.5264	0.1331	0.5307	0.522
2.7853	4.0	9996	2.3945	0.4879	0.1191	0.4871	0.4811
2.7221	5.0	12495	2.3678	0.5655	0.0981	0.5672	0.5595
2.6797	6.0	14994	2.3511	0.5002	0.1191	0.5084	0.4968
2.6516	7.0	17493	2.3409	0.5606	0.1138	0.5631	0.5578
2.6364	8.0	19992	2.3401	0.5417	0.0921	0.5445	0.5404

Framework versions

Transformers 4.27.4
Pytorch 1.13.0
Datasets 2.1.0
Tokenizers 0.13.2