pytorch tensorboard t5 text2text-generation dataset:snli transformers summarization generated_from_trainer license:apache-2.0 model-index autotrain_compatible
---
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: 34.4237
---

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# 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: 2.0458
- Rouge1: 34.4237
- Rouge2: 14.5442
- Rougel: 32.5483
- Rougelsum: 32.5785

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 1.8605        | 1.0   | 2863  | 2.0813          | 34.4597 | 14.5186 | 32.6909 | 32.7097   |
| 1.9209        | 2.0   | 5726  | 2.0721          | 34.3859 | 14.5733 | 32.5188 | 32.5524   |
| 1.9367        | 3.0   | 8589  | 2.0623          | 34.4192 | 14.455  | 32.581  | 32.5962   |
| 1.9539        | 4.0   | 11452 | 2.0565          | 34.5148 | 14.6131 | 32.6786 | 32.7174   |
| 1.9655        | 5.0   | 14315 | 2.0538          | 34.4393 | 14.6439 | 32.6344 | 32.6587   |
| 1.9683        | 6.0   | 17178 | 2.0493          | 34.7199 | 14.7763 | 32.8625 | 32.8782   |
| 1.9735        | 7.0   | 20041 | 2.0476          | 34.5366 | 14.6362 | 32.6939 | 32.7177   |
| 1.98          | 8.0   | 22904 | 2.0458          | 34.5    | 14.5695 | 32.6219 | 32.6478   |


### Framework versions

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