transformers tensorboard safetensors t5 text2text-generation generated_from_trainer base_model:t5-small license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: summarizer-billsum_dataset
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# summarizer-billsum_dataset

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4835
- Rouge1: 0.1837
- Rouge2: 0.0818
- Rougel: 0.1536
- Rougelsum: 0.154
- 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: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 25   | 3.4284          | 0.1297 | 0.0383 | 0.109  | 0.1089    | 19.0    |
| No log        | 2.0   | 50   | 3.0057          | 0.1222 | 0.0351 | 0.1031 | 0.1029    | 19.0    |
| No log        | 3.0   | 75   | 2.8213          | 0.1242 | 0.0376 | 0.1042 | 0.1041    | 19.0    |
| No log        | 4.0   | 100  | 2.7231          | 0.1283 | 0.0401 | 0.105  | 0.105     | 19.0    |
| No log        | 5.0   | 125  | 2.6706          | 0.1371 | 0.049  | 0.1122 | 0.1122    | 19.0    |
| No log        | 6.0   | 150  | 2.6307          | 0.1373 | 0.0473 | 0.1129 | 0.1128    | 19.0    |
| No log        | 7.0   | 175  | 2.5988          | 0.1408 | 0.0496 | 0.1149 | 0.1148    | 19.0    |
| No log        | 8.0   | 200  | 2.5731          | 0.1471 | 0.0509 | 0.1209 | 0.1212    | 19.0    |
| No log        | 9.0   | 225  | 2.5557          | 0.156  | 0.0584 | 0.1293 | 0.1296    | 19.0    |
| No log        | 10.0  | 250  | 2.5382          | 0.1642 | 0.0656 | 0.1357 | 0.1356    | 19.0    |
| No log        | 11.0  | 275  | 2.5262          | 0.1695 | 0.0716 | 0.1402 | 0.1403    | 19.0    |
| No log        | 12.0  | 300  | 2.5173          | 0.1773 | 0.0778 | 0.1475 | 0.1475    | 19.0    |
| No log        | 13.0  | 325  | 2.5089          | 0.18   | 0.0801 | 0.1493 | 0.1496    | 19.0    |
| No log        | 14.0  | 350  | 2.5013          | 0.1821 | 0.08   | 0.1515 | 0.1516    | 19.0    |
| No log        | 15.0  | 375  | 2.4954          | 0.1823 | 0.0801 | 0.1527 | 0.1528    | 19.0    |
| No log        | 16.0  | 400  | 2.4910          | 0.1832 | 0.0808 | 0.1532 | 0.1534    | 19.0    |
| No log        | 17.0  | 425  | 2.4875          | 0.1842 | 0.082  | 0.154  | 0.1543    | 19.0    |
| No log        | 18.0  | 450  | 2.4849          | 0.1841 | 0.0818 | 0.1539 | 0.1541    | 19.0    |
| No log        | 19.0  | 475  | 2.4840          | 0.1837 | 0.0818 | 0.1536 | 0.154     | 19.0    |
| 2.7815        | 20.0  | 500  | 2.4835          | 0.1837 | 0.0818 | 0.1536 | 0.154     | 19.0    |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
