metadata
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
datasets:
- xlsum
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-summary
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: xlsum
type: xlsum
config: french
split: validation
args: french
metrics:
- name: Rouge1
type: rouge
value: 21.6196
mt5-small-finetuned-summary
This model is a fine-tuned version of google/mt5-small on the xlsum dataset. It achieves the following results on the evaluation set:
- Loss: 2.1466
- Rouge1: 21.6196
- Rouge2: 7.7979
- Rougel: 17.5683
- Rougelsum: 17.6757
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: 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: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 3.9629 | 1.0 | 2170 | 2.3132 | 20.7316 | 7.3431 | 16.9157 | 17.0149 |
| 2.9704 | 2.0 | 4340 | 2.2299 | 21.3148 | 7.8529 | 17.2968 | 17.3873 |
| 2.8026 | 3.0 | 6510 | 2.2092 | 21.3313 | 7.8526 | 17.3679 | 17.4773 |
| 2.7054 | 4.0 | 8680 | 2.1876 | 21.6909 | 7.9841 | 17.6881 | 17.7839 |
| 2.6453 | 5.0 | 10850 | 2.1743 | 21.7372 | 7.7546 | 17.6551 | 17.7575 |
| 2.5925 | 6.0 | 13020 | 2.1602 | 21.5715 | 7.7879 | 17.5943 | 17.6994 |
| 2.5619 | 7.0 | 15190 | 2.1482 | 21.5888 | 7.8789 | 17.6519 | 17.752 |
| 2.5415 | 8.0 | 17360 | 2.1466 | 21.6196 | 7.7979 | 17.5683 | 17.6757 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0