transformers pytorch tensorboard t5 text2text-generation generated_from_trainer dataset:billsum license:apache-2.0 model-index autotrain_compatible text-generation-inference endpoints_compatible region:us
---
datasets:
- billsum
license: apache-2.0
metrics:
- rouge
tags:
- generated_from_trainer
model-index:
- name: Text_Summarization
  results:
  - task:
      type: text2text-generation
      name: Sequence-to-sequence Language Modeling
    dataset:
      name: billsum
      type: billsum
      config: default
      split: ca_test
      args: default
    metrics:
    - type: rouge
      value: 0.1324
      name: Rouge1
---

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# Text_Summarization

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the billsum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7235
- Rouge1: 0.1324
- Rouge2: 0.0397
- Rougel: 0.1114
- Rougelsum: 0.111
- 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: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 74   | 2.8406          | 0.1286 | 0.04   | 0.1087 | 0.1088    | 19.0    |
| No log        | 2.0   | 148  | 2.7235          | 0.1324 | 0.0397 | 0.1114 | 0.111     | 19.0    |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
