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: 22.1761
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: 2.2770
- Rouge1: 22.1761
- Rouge2: 8.0115
- Rougel: 18.8245
- Rougelsum: 18.8574
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 |
|---|---|---|---|---|---|---|---|
| 4.7862 | 1.0 | 1085 | 2.5085 | 21.2935 | 7.4006 | 18.0791 | 18.0868 |
| 3.2212 | 2.0 | 2170 | 2.4069 | 21.968 | 7.9139 | 18.5785 | 18.6248 |
| 3.0201 | 3.0 | 3255 | 2.3489 | 21.8529 | 7.9865 | 18.6842 | 18.7074 |
| 2.9085 | 4.0 | 4340 | 2.3173 | 22.1605 | 8.2646 | 18.8284 | 18.838 |
| 2.8285 | 5.0 | 5425 | 2.2965 | 22.0612 | 8.0447 | 18.7454 | 18.7784 |
| 2.7727 | 6.0 | 6510 | 2.2899 | 22.1416 | 7.9747 | 18.7622 | 18.8029 |
| 2.7311 | 7.0 | 7595 | 2.2797 | 22.2979 | 8.1382 | 18.9798 | 19.035 |
| 2.7171 | 8.0 | 8680 | 2.2770 | 22.1761 | 8.0115 | 18.8245 | 18.8574 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0