metadata
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- snli
metrics:
- rouge
model-index:
- name: t5-small-finetuned-contradiction
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: snli
type: snli
args: plain_text
metrics:
- name: Rouge1
type: rouge
value: 34.3638
t5-small-finetuned-contradiction
This model is a fine-tuned version of domenicrosati/t5-small-finetuned-contradiction on the snli dataset. It achieves the following results on the evaluation set:
- Loss: 2.1269
- Rouge1: 34.3638
- Rouge2: 14.7916
- Rougel: 32.6308
- Rougelsum: 32.6288
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 2.1984 | 1.0 | 2863 | 2.1556 | 34.4429 | 14.6791 | 32.5812 | 32.5896 |
| 2.2085 | 2.0 | 5726 | 2.1390 | 34.3719 | 14.731 | 32.5979 | 32.5949 |
| 2.188 | 3.0 | 8589 | 2.1302 | 34.4276 | 14.7191 | 32.62 | 32.6132 |
| 2.1768 | 4.0 | 11452 | 2.1269 | 34.4408 | 14.8235 | 32.7067 | 32.7065 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0+cu102
- Datasets 2.1.0
- Tokenizers 0.12.1