---
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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2397
- Rouge1: 39.9145
- Rouge2: 33.183
- Rougel: 39.9484
- Rougelsum: 39.9376
- 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   | 90   | 3.4654          | 9.8007  | 0.2231  | 9.4993  | 9.501     | 18.6889 |
| No log        | 2.0   | 180  | 2.1906          | 10.4443 | 0.2158  | 9.8828  | 9.8755    | 18.8972 |
| No log        | 3.0   | 270  | 1.3067          | 11.7213 | 0.5145  | 10.913  | 10.9345   | 18.8528 |
| No log        | 4.0   | 360  | 0.7369          | 14.9807 | 1.4227  | 13.7179 | 13.7131   | 18.8333 |
| No log        | 5.0   | 450  | 0.6143          | 19.8511 | 4.6089  | 18.0244 | 17.9558   | 18.7083 |
| 2.447         | 6.0   | 540  | 0.5312          | 23.1026 | 8.6515  | 20.7866 | 20.757    | 18.7139 |
| 2.447         | 7.0   | 630  | 0.4782          | 21.9961 | 9.3626  | 19.7651 | 19.7488   | 18.5944 |
| 2.447         | 8.0   | 720  | 0.4365          | 16.4406 | 6.5397  | 14.9694 | 14.9816   | 18.6639 |
| 2.447         | 9.0   | 810  | 0.3603          | 6.9337  | 3.7397  | 6.6337  | 6.6621    | 18.9028 |
| 2.447         | 10.0  | 900  | 0.2696          | 24.2884 | 19.0601 | 24.1044 | 24.1488   | 18.9694 |
| 2.447         | 11.0  | 990  | 0.2590          | 39.2002 | 32.3107 | 39.202  | 39.1928   | 19.0    |
| 0.572         | 12.0  | 1080 | 0.2546          | 39.0083 | 32.1464 | 39.0296 | 38.9988   | 19.0    |
| 0.572         | 13.0  | 1170 | 0.2486          | 39.519  | 32.7114 | 39.5614 | 39.5391   | 19.0    |
| 0.572         | 14.0  | 1260 | 0.2465          | 39.589  | 32.8014 | 39.6298 | 39.6092   | 19.0    |
| 0.572         | 15.0  | 1350 | 0.2444          | 39.5831 | 32.7959 | 39.6266 | 39.6123   | 19.0    |
| 0.572         | 16.0  | 1440 | 0.2427          | 39.7174 | 32.9525 | 39.7513 | 39.7311   | 19.0    |
| 0.3469        | 17.0  | 1530 | 0.2412          | 39.8478 | 33.0999 | 39.8901 | 39.8708   | 19.0    |
| 0.3469        | 18.0  | 1620 | 0.2401          | 39.8528 | 33.1031 | 39.8819 | 39.873    | 19.0    |
| 0.3469        | 19.0  | 1710 | 0.2398          | 39.9283 | 33.1964 | 39.9502 | 39.9533   | 19.0    |
| 0.3469        | 20.0  | 1800 | 0.2397          | 39.9145 | 33.183  | 39.9484 | 39.9376   | 19.0    |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2