metadata
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- wiki_lingua
metrics:
- rouge
model-index:
- name: wiki_lingua-id-8-3-5.6e-05-mt5-small-finetuned
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: wiki_lingua
type: wiki_lingua
config: id
split: test
args: id
metrics:
- name: Rouge1
type: rouge
value: 18.0064
wiki_lingua-id-8-3-5.6e-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: 2.3388
- Rouge1: 18.0064
- Rouge2: 5.5315
- Rougel: 16.1048
- Rougelsum: 17.6763
Baseline LEAD-64
- Rouge1: 20.32
- Rouge2: 4.94
- Rougel: 14.0
- Rougelsum: 14.0
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: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
---|---|---|---|---|---|---|---|
3.4701 | 1.0 | 4029 | 2.4403 | 17.0314 | 5.0932 | 15.3277 | 16.713 |
2.8067 | 2.0 | 8058 | 2.3568 | 17.6738 | 5.3508 | 15.8002 | 17.336 |
2.7095 | 3.0 | 12087 | 2.3388 | 18.0064 | 5.5315 | 16.1048 | 17.6763 |
Framework versions
- Transformers 4.27.4
- Pytorch 1.13.0
- Datasets 2.1.0
- Tokenizers 0.13.2