---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: my_awesome_sumarize_model
  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. -->

# my_awesome_sumarize_model

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: 1.2464
- Rouge1: 0.3573
- Rouge2: 0.2493
- Rougel: 0.3411
- Rougelsum: 0.3387
- 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   | 4    | 1.2873          | 0.3626 | 0.2514 | 0.3512 | 0.3486    | 19.0    |
| No log        | 2.0   | 8    | 1.2838          | 0.3542 | 0.2441 | 0.3452 | 0.3428    | 19.0    |
| No log        | 3.0   | 12   | 1.2756          | 0.3542 | 0.2441 | 0.3452 | 0.3428    | 19.0    |
| No log        | 4.0   | 16   | 1.2679          | 0.3542 | 0.2441 | 0.3452 | 0.3428    | 19.0    |
| No log        | 5.0   | 20   | 1.2627          | 0.3542 | 0.2441 | 0.3452 | 0.3428    | 19.0    |
| No log        | 6.0   | 24   | 1.2608          | 0.3542 | 0.2441 | 0.3452 | 0.3428    | 19.0    |
| No log        | 7.0   | 28   | 1.2587          | 0.3542 | 0.2441 | 0.3452 | 0.3428    | 19.0    |
| No log        | 8.0   | 32   | 1.2576          | 0.359  | 0.2495 | 0.346  | 0.3428    | 19.0    |
| No log        | 9.0   | 36   | 1.2569          | 0.359  | 0.2495 | 0.346  | 0.3428    | 19.0    |
| No log        | 10.0  | 40   | 1.2558          | 0.359  | 0.2495 | 0.346  | 0.3428    | 19.0    |
| No log        | 11.0  | 44   | 1.2537          | 0.359  | 0.2495 | 0.346  | 0.3428    | 19.0    |
| No log        | 12.0  | 48   | 1.2521          | 0.3573 | 0.2493 | 0.3411 | 0.3387    | 19.0    |
| No log        | 13.0  | 52   | 1.2500          | 0.3573 | 0.2493 | 0.3411 | 0.3387    | 19.0    |
| No log        | 14.0  | 56   | 1.2486          | 0.3573 | 0.2493 | 0.3411 | 0.3387    | 19.0    |
| No log        | 15.0  | 60   | 1.2476          | 0.3573 | 0.2493 | 0.3411 | 0.3387    | 19.0    |
| No log        | 16.0  | 64   | 1.2474          | 0.3573 | 0.2493 | 0.3411 | 0.3387    | 19.0    |
| No log        | 17.0  | 68   | 1.2468          | 0.3573 | 0.2493 | 0.3411 | 0.3387    | 19.0    |
| No log        | 18.0  | 72   | 1.2465          | 0.3573 | 0.2493 | 0.3411 | 0.3387    | 19.0    |
| No log        | 19.0  | 76   | 1.2463          | 0.3573 | 0.2493 | 0.3411 | 0.3387    | 19.0    |
| No log        | 20.0  | 80   | 1.2464          | 0.3573 | 0.2493 | 0.3411 | 0.3387    | 19.0    |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2