---
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: 1.2874
- Rouge1: 0.3656
- Rouge2: 0.2555
- Rougel: 0.3544
- Rougelsum: 0.3512
- 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    | 1.4360          | 0.3727 | 0.2518 | 0.3419 | 0.3401    | 19.0    |
| No log        | 2.0   | 8    | 1.4087          | 0.3389 | 0.2309 | 0.3249 | 0.3216    | 18.65   |
| No log        | 3.0   | 12   | 1.3843          | 0.3389 | 0.2309 | 0.3249 | 0.3216    | 18.65   |
| No log        | 4.0   | 16   | 1.3659          | 0.355  | 0.2429 | 0.3394 | 0.3373    | 19.0    |
| No log        | 5.0   | 20   | 1.3533          | 0.3656 | 0.251  | 0.3489 | 0.3474    | 19.0    |
| No log        | 6.0   | 24   | 1.3431          | 0.3761 | 0.2618 | 0.3599 | 0.3569    | 19.0    |
| No log        | 7.0   | 28   | 1.3323          | 0.3761 | 0.2618 | 0.3599 | 0.3569    | 19.0    |
| No log        | 8.0   | 32   | 1.3239          | 0.3764 | 0.2667 | 0.3651 | 0.362     | 19.0    |
| No log        | 9.0   | 36   | 1.3174          | 0.3656 | 0.2555 | 0.3544 | 0.3512    | 19.0    |
| No log        | 10.0  | 40   | 1.3113          | 0.3656 | 0.2555 | 0.3544 | 0.3512    | 19.0    |
| No log        | 11.0  | 44   | 1.3061          | 0.3656 | 0.2555 | 0.3544 | 0.3512    | 19.0    |
| No log        | 12.0  | 48   | 1.3024          | 0.3656 | 0.2555 | 0.3544 | 0.3512    | 19.0    |
| No log        | 13.0  | 52   | 1.2983          | 0.3656 | 0.2555 | 0.3544 | 0.3512    | 19.0    |
| No log        | 14.0  | 56   | 1.2949          | 0.3656 | 0.2555 | 0.3544 | 0.3512    | 19.0    |
| No log        | 15.0  | 60   | 1.2921          | 0.3656 | 0.2555 | 0.3544 | 0.3512    | 19.0    |
| No log        | 16.0  | 64   | 1.2904          | 0.3656 | 0.2555 | 0.3544 | 0.3512    | 19.0    |
| No log        | 17.0  | 68   | 1.2890          | 0.3656 | 0.2555 | 0.3544 | 0.3512    | 19.0    |
| No log        | 18.0  | 72   | 1.2881          | 0.3656 | 0.2555 | 0.3544 | 0.3512    | 19.0    |
| No log        | 19.0  | 76   | 1.2876          | 0.3656 | 0.2555 | 0.3544 | 0.3512    | 19.0    |
| No log        | 20.0  | 80   | 1.2874          | 0.3656 | 0.2555 | 0.3544 | 0.3512    | 19.0    |


### Framework versions

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