---
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: 34.4713
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# t5-small-finetuned-contradiction

This model is a fine-tuned version of [domenicrosati/t5-small-finetuned-contradiction](https://huggingface.co/domenicrosati/t5-small-finetuned-contradiction) on the snli dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0524
- Rouge1: 34.4713
- Rouge2: 14.6253
- Rougel: 32.5971
- Rougelsum: 32.5854

## 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: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 1.9316        | 1.0   | 2863  | 2.0832          | 34.5611 | 14.5831 | 32.7994 | 32.7887   |
| 1.9898        | 2.0   | 5726  | 2.0742          | 34.4883 | 14.6727 | 32.6392 | 32.6204   |
| 1.9995        | 3.0   | 8589  | 2.0658          | 34.6327 | 14.6086 | 32.7722 | 32.7524   |
| 2.0108        | 4.0   | 11452 | 2.0602          | 34.6013 | 14.6843 | 32.7286 | 32.7192   |
| 2.0165        | 5.0   | 14315 | 2.0581          | 34.5423 | 14.6649 | 32.705  | 32.6891   |
| 2.0132        | 6.0   | 17178 | 2.0545          | 34.6902 | 14.7817 | 32.8538 | 32.8374   |
| 2.0128        | 7.0   | 20041 | 2.0537          | 34.5965 | 14.691  | 32.7323 | 32.7165   |
| 2.0139        | 8.0   | 22904 | 2.0524          | 34.529  | 14.6524 | 32.6635 | 32.6443   |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0+cu102
- Datasets 2.1.0
- Tokenizers 0.12.1