---
license: apache-2.0
base_model: google-t5/t5-small
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-small-finetuned
  results: []
pipeline_tag: summarization
---

<!-- 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

This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 13.3545
- Rouge1: 0.0324
- Rouge2: 0.0035
- Rougel: 0.0283
- Rougelsum: 0.0297

## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| No log        | 0.67  | 1    | 25.3754         | 0.0458 | 0.0078 | 0.038  | 0.0396    |
| No log        | 2.0   | 3    | 23.7399         | 0.0458 | 0.0078 | 0.038  | 0.0396    |
| No log        | 2.67  | 4    | 22.8640         | 0.0442 | 0.0053 | 0.0367 | 0.0384    |
| No log        | 4.0   | 6    | 21.0827         | 0.0442 | 0.0053 | 0.0367 | 0.0384    |
| No log        | 4.67  | 7    | 20.1867         | 0.0442 | 0.0053 | 0.0367 | 0.0384    |
| No log        | 6.0   | 9    | 18.3401         | 0.0431 | 0.0109 | 0.0368 | 0.0388    |
| No log        | 6.67  | 10   | 17.5540         | 0.0405 | 0.0054 | 0.0343 | 0.0346    |
| No log        | 8.0   | 12   | 16.5123         | 0.0405 | 0.0054 | 0.0343 | 0.0346    |
| No log        | 8.67  | 13   | 16.2865         | 0.0405 | 0.0054 | 0.0343 | 0.0346    |
| No log        | 10.0  | 15   | 15.9394         | 0.0405 | 0.0054 | 0.0343 | 0.0346    |
| No log        | 10.67 | 16   | 15.7787         | 0.0405 | 0.0054 | 0.0343 | 0.0346    |
| No log        | 12.0  | 18   | 15.4614         | 0.0406 | 0.004  | 0.0331 | 0.0361    |
| No log        | 12.67 | 19   | 15.3169         | 0.037  | 0.0012 | 0.0288 | 0.032     |
| 17.4357       | 14.0  | 21   | 15.0546         | 0.0372 | 0.0023 | 0.0302 | 0.0345    |
| 17.4357       | 14.67 | 22   | 14.9349         | 0.0372 | 0.0023 | 0.0302 | 0.0345    |
| 17.4357       | 16.0  | 24   | 14.7097         | 0.0372 | 0.0023 | 0.0302 | 0.0345    |
| 17.4357       | 16.67 | 25   | 14.6033         | 0.0372 | 0.0023 | 0.0302 | 0.0345    |
| 17.4357       | 18.0  | 27   | 14.4049         | 0.0365 | 0.0023 | 0.0298 | 0.0337    |
| 17.4357       | 18.67 | 28   | 14.3124         | 0.0365 | 0.0023 | 0.0298 | 0.0337    |
| 17.4357       | 20.0  | 30   | 14.1419         | 0.0324 | 0.0023 | 0.0271 | 0.0296    |
| 17.4357       | 20.67 | 31   | 14.0635         | 0.0324 | 0.0023 | 0.0272 | 0.0297    |
| 17.4357       | 22.0  | 33   | 13.9163         | 0.0324 | 0.0023 | 0.0272 | 0.0297    |
| 17.4357       | 22.67 | 34   | 13.8491         | 0.0324 | 0.0023 | 0.0272 | 0.0297    |
| 17.4357       | 24.0  | 36   | 13.7281         | 0.0324 | 0.0023 | 0.0272 | 0.0297    |
| 17.4357       | 24.67 | 37   | 13.6752         | 0.0324 | 0.0023 | 0.0272 | 0.0297    |
| 17.4357       | 26.0  | 39   | 13.5841         | 0.0324 | 0.0023 | 0.0272 | 0.0297    |
| 13.2934       | 26.67 | 40   | 13.5448         | 0.0324 | 0.0023 | 0.0272 | 0.0297    |
| 13.2934       | 28.0  | 42   | 13.4779         | 0.0324 | 0.0023 | 0.0272 | 0.0297    |
| 13.2934       | 28.67 | 43   | 13.4500         | 0.0324 | 0.0023 | 0.0272 | 0.0297    |
| 13.2934       | 30.0  | 45   | 13.4051         | 0.0324 | 0.0035 | 0.0283 | 0.0297    |
| 13.2934       | 30.67 | 46   | 13.3881         | 0.0324 | 0.0035 | 0.0283 | 0.0297    |
| 13.2934       | 32.0  | 48   | 13.3645         | 0.0324 | 0.0035 | 0.0283 | 0.0297    |
| 13.2934       | 32.67 | 49   | 13.3578         | 0.0324 | 0.0035 | 0.0283 | 0.0297    |
| 13.2934       | 33.33 | 50   | 13.3545         | 0.0324 | 0.0035 | 0.0283 | 0.0297    |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.2.0
- Datasets 2.16.1
- Tokenizers 0.15.1