metadata

license: apache-2.0
base_model: google/mt5-base
tags:
  - summarization
  - generated_from_trainer
datasets:
  - xlsum
metrics:
  - rouge
model-index:
  - name: mt5-base-xlsum
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: xlsum
          type: xlsum
          config: ukrainian
          split: train
          args: ukrainian
        metrics:
          - name: Rouge1
            type: rouge
            value: 2.98

mt5-base-xlsum

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

Loss: 2.0396
Rouge1: 2.98
Rouge2: 0.1333
Rougel: 3.0267
Rougelsum: 2.9933

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: 2
eval_batch_size: 2
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
5.3745	1.0	500	2.5041	1.0696	0.13	1.062	1.0629
3.413	2.0	1000	2.2178	1.8333	0.1333	1.84	1.8633
3.1052	3.0	1500	2.0844	3.14	0.2667	3.18	3.1733
2.9673	4.0	2000	2.0396	2.98	0.1333	3.0267	2.9933

Framework versions

Transformers 4.34.0
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.14.1