metadata
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
datasets:
- mlsum
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-mlsum
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: mlsum
type: mlsum
config: fr
split: validation
args: fr
metrics:
- name: Rouge1
type: rouge
value: 23.8523
mt5-small-finetuned-mlsum
This model is a fine-tuned version of google/mt5-small on the mlsum dataset. It achieves the following results on the evaluation set:
- Loss: 2.1938
- Rouge1: 23.8523
- Rouge2: 11.7959
- Rougel: 21.1838
- Rougelsum: 21.2463
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 5.6087 | 1.0 | 1005 | 2.4269 | 29.6042 | 15.5378 | 25.5964 | 25.6503 |
| 3.4099 | 2.0 | 2010 | 2.2734 | 23.8963 | 12.2351 | 21.4806 | 21.4861 |
| 3.169 | 3.0 | 3015 | 2.2310 | 26.7408 | 13.7129 | 23.7543 | 23.8443 |
| 3.0327 | 4.0 | 4020 | 2.2084 | 23.2971 | 11.5675 | 20.911 | 21.0564 |
| 2.9777 | 5.0 | 5025 | 2.1938 | 23.8523 | 11.7959 | 21.1838 | 21.2463 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1