transformers pytorch tensorboard t5 text2text-generation summarization generated_from_trainer dataset:cnn_dailymail license:apache-2.0 model-index autotrain_compatible text-generation-inference endpoints_compatible region:us
---
datasets:
- cnn_dailymail
license: apache-2.0
metrics:
- rouge
tags:
- summarization
- generated_from_trainer
model-index:
- name: t5-small-finetuned-cnn-v2
  results:
  - task:
      type: text2text-generation
      name: Sequence-to-sequence Language Modeling
    dataset:
      name: cnn_dailymail
      type: cnn_dailymail
      args: 3.0.0
    metrics:
    - type: rouge
      value: 35.154
      name: Rouge1
---

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# t5-small-finetuned-cnn-v2

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the cnn_dailymail dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5474
- Rouge1: 35.154
- Rouge2: 18.683
- Rougel: 30.8481
- Rougelsum: 32.9638

## 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: 8

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:------:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 1.8823        | 1.0   | 35890  | 1.5878          | 34.9676 | 18.4927 | 30.6753 | 32.7702   |
| 1.7871        | 2.0   | 71780  | 1.5709          | 34.9205 | 18.5556 | 30.6514 | 32.745    |
| 1.7507        | 3.0   | 107670 | 1.5586          | 34.9825 | 18.4964 | 30.6724 | 32.7644   |
| 1.7253        | 4.0   | 143560 | 1.5584          | 35.074  | 18.6171 | 30.8007 | 32.9132   |
| 1.705         | 5.0   | 179450 | 1.5528          | 35.023  | 18.5787 | 30.7014 | 32.8396   |
| 1.6894        | 6.0   | 215340 | 1.5518          | 35.0583 | 18.6754 | 30.791  | 32.8814   |
| 1.6776        | 7.0   | 251230 | 1.5468          | 35.2236 | 18.6812 | 30.8944 | 33.0362   |
| 1.6687        | 8.0   | 287120 | 1.5474          | 35.154  | 18.683  | 30.8481 | 32.9638   |


### Framework versions

- Transformers 4.14.0
- Pytorch 1.5.0
- Datasets 2.3.2
- Tokenizers 0.10.3
