metadata
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
datasets:
- eur-lex-sum
metrics:
- rouge
model-index:
- name: T5_small_eurlexsum
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: eur-lex-sum
type: eur-lex-sum
config: french
split: test
args: french
metrics:
- name: Rouge1
type: rouge
value: 0.2
T5_small_eurlexsum
This model is a fine-tuned version of t5-small on the eur-lex-sum dataset. It achieves the following results on the evaluation set:
- Loss: 1.1159
- Rouge1: 0.2
- Rouge2: 0.1394
- Rougel: 0.1833
- Rougelsum: 0.1829
- Gen Len: 19.0
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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 | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 71 | 1.4740 | 0.1718 | 0.0935 | 0.1476 | 0.1476 | 19.0 |
| No log | 2.0 | 142 | 1.2138 | 0.1915 | 0.1207 | 0.1719 | 0.1719 | 19.0 |
| No log | 3.0 | 213 | 1.1368 | 0.1953 | 0.1306 | 0.1759 | 0.1759 | 19.0 |
| No log | 4.0 | 284 | 1.1159 | 0.2 | 0.1394 | 0.1833 | 0.1829 | 19.0 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.0
- Tokenizers 0.13.3