transformers tensorboard safetensors t5 text2text-generation generated_from_trainer dataset:billsum base_model:t5-small license:apache-2.0 model-index autotrain_compatible endpoints_compatible text-generation-inference region:us
---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
datasets:
- billsum
metrics:
- rouge
model-index:
- name: t5
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: billsum
      type: billsum
      config: default
      split: ca_test
      args: default
    metrics:
    - name: Rouge1
      type: rouge
      value: 0.1248
---

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# t5

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: 2.0846
- Rouge1: 0.1248
- Rouge2: 0.0719
- Rougel: 0.1096
- Rougelsum: 0.1097
- 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: 4
- eval_batch_size: 4
- 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 | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 248  | 2.3488          | 0.0936 | 0.0361 | 0.0801 | 0.0799    | 19.0    |
| No log        | 2.0   | 496  | 2.2214          | 0.1098 | 0.0519 | 0.0953 | 0.0953    | 19.0    |
| 2.8859        | 3.0   | 744  | 2.1603          | 0.1243 | 0.0682 | 0.1082 | 0.1081    | 19.0    |
| 2.8859        | 4.0   | 992  | 2.1276          | 0.1255 | 0.0717 | 0.1098 | 0.1099    | 19.0    |
| 2.3699        | 5.0   | 1240 | 2.1063          | 0.1252 | 0.0715 | 0.1101 | 0.1102    | 19.0    |
| 2.3699        | 6.0   | 1488 | 2.0908          | 0.1254 | 0.0723 | 0.1099 | 0.1101    | 19.0    |
| 2.2841        | 7.0   | 1736 | 2.0862          | 0.1247 | 0.0718 | 0.1093 | 0.1094    | 19.0    |
| 2.2841        | 8.0   | 1984 | 2.0846          | 0.1248 | 0.0719 | 0.1096 | 0.1097    | 19.0    |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
