---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-small-finetuned-xsum
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# t5-small-finetuned-xsum

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1208
- Rouge1: 36.9538
- Rouge2: 20.7839
- Rougel: 37.3871
- Rougelsum: 37.2811
- Gen Len: 18.8846

## 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: 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: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log        | 1.0   | 26   | 3.4305          | 23.5049 | 10.2407 | 21.4449 | 21.9379   | 19.0    |
| No log        | 2.0   | 52   | 3.1134          | 24.9063 | 11.6883 | 22.8747 | 23.4655   | 18.9615 |
| No log        | 3.0   | 78   | 2.8933          | 27.804  | 14.238  | 26.2818 | 26.6659   | 18.9615 |
| No log        | 4.0   | 104  | 2.7254          | 32.7867 | 18.1634 | 32.9538 | 32.9732   | 18.9231 |
| No log        | 5.0   | 130  | 2.6139          | 33.4273 | 18.5316 | 33.4935 | 33.5047   | 18.8462 |
| No log        | 6.0   | 156  | 2.5310          | 33.3767 | 18.518  | 33.4835 | 33.4465   | 18.8462 |
| No log        | 7.0   | 182  | 2.4648          | 34.8591 | 19.4604 | 35.0391 | 35.109    | 18.8462 |
| No log        | 8.0   | 208  | 2.4072          | 36.9403 | 20.5598 | 37.2531 | 37.3462   | 18.8462 |
| No log        | 9.0   | 234  | 2.3542          | 37.9145 | 21.2925 | 38.315  | 38.2661   | 18.8462 |
| No log        | 10.0  | 260  | 2.3046          | 37.9145 | 21.2925 | 38.315  | 38.2661   | 18.8462 |
| No log        | 11.0  | 286  | 2.2666          | 37.85   | 21.3084 | 38.1072 | 38.1338   | 18.8462 |
| No log        | 12.0  | 312  | 2.2340          | 37.85   | 21.4208 | 38.1072 | 38.1338   | 18.8462 |
| No log        | 13.0  | 338  | 2.2060          | 37.85   | 21.4208 | 38.1072 | 38.1338   | 18.8462 |
| No log        | 14.0  | 364  | 2.1830          | 37.8604 | 21.4465 | 38.1781 | 38.1837   | 18.8462 |
| No log        | 15.0  | 390  | 2.1646          | 37.8604 | 21.4465 | 38.1781 | 38.1837   | 18.8846 |
| No log        | 16.0  | 416  | 2.1500          | 36.9538 | 20.7839 | 37.3871 | 37.2811   | 18.8846 |
| No log        | 17.0  | 442  | 2.1359          | 36.9538 | 20.7839 | 37.3871 | 37.2811   | 18.8846 |
| No log        | 18.0  | 468  | 2.1278          | 36.9538 | 20.7839 | 37.3871 | 37.2811   | 18.8846 |
| No log        | 19.0  | 494  | 2.1227          | 36.9538 | 20.7839 | 37.3871 | 37.2811   | 18.8846 |
| 2.6902        | 20.0  | 520  | 2.1208          | 36.9538 | 20.7839 | 37.3871 | 37.2811   | 18.8846 |


### Framework versions

- Transformers 4.36.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0