---
license: apache-2.0
base_model: t5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: T5_base_title_v3
  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_base_title_v3

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8544
- Rouge1: 0.4104
- Rouge2: 0.212
- Rougel: 0.3579
- Rougelsum: 0.3576
- Gen Len: 16.585

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.2216        | 1.0   | 500   | 1.9241          | 0.3884 | 0.1992 | 0.3375 | 0.3371    | 16.168  |
| 1.9818        | 2.0   | 1000  | 1.8699          | 0.391  | 0.2002 | 0.342  | 0.341     | 16.386  |
| 1.8876        | 3.0   | 1500  | 1.8377          | 0.3972 | 0.2033 | 0.3447 | 0.3434    | 16.635  |
| 1.805         | 4.0   | 2000  | 1.8202          | 0.3981 | 0.2061 | 0.3482 | 0.3477    | 16.213  |
| 1.7422        | 5.0   | 2500  | 1.8180          | 0.395  | 0.2051 | 0.345  | 0.3445    | 16.74   |
| 1.6919        | 6.0   | 3000  | 1.8154          | 0.4042 | 0.2091 | 0.3526 | 0.3519    | 16.197  |
| 1.6426        | 7.0   | 3500  | 1.8160          | 0.4048 | 0.2094 | 0.3509 | 0.3506    | 16.546  |
| 1.5982        | 8.0   | 4000  | 1.8224          | 0.4088 | 0.2131 | 0.3556 | 0.3552    | 16.516  |
| 1.5615        | 9.0   | 4500  | 1.8219          | 0.4079 | 0.2121 | 0.3549 | 0.3545    | 16.474  |
| 1.5304        | 10.0  | 5000  | 1.8235          | 0.4059 | 0.2128 | 0.3548 | 0.3547    | 16.498  |
| 1.4996        | 11.0  | 5500  | 1.8299          | 0.4098 | 0.211  | 0.3569 | 0.3564    | 16.378  |
| 1.4735        | 12.0  | 6000  | 1.8349          | 0.4108 | 0.2129 | 0.3576 | 0.3572    | 16.672  |
| 1.4502        | 13.0  | 6500  | 1.8373          | 0.4103 | 0.2132 | 0.3566 | 0.3565    | 16.68   |
| 1.426         | 14.0  | 7000  | 1.8434          | 0.4092 | 0.2104 | 0.3559 | 0.3554    | 16.669  |
| 1.4137        | 15.0  | 7500  | 1.8442          | 0.4117 | 0.212  | 0.358  | 0.3576    | 16.547  |
| 1.401         | 16.0  | 8000  | 1.8503          | 0.4109 | 0.2126 | 0.3569 | 0.3567    | 16.552  |
| 1.3901        | 17.0  | 8500  | 1.8517          | 0.4115 | 0.2146 | 0.3601 | 0.36      | 16.553  |
| 1.3817        | 18.0  | 9000  | 1.8539          | 0.4104 | 0.2118 | 0.3572 | 0.3573    | 16.588  |
| 1.3696        | 19.0  | 9500  | 1.8553          | 0.4103 | 0.2126 | 0.3581 | 0.3578    | 16.568  |
| 1.369         | 20.0  | 10000 | 1.8544          | 0.4104 | 0.212  | 0.3579 | 0.3576    | 16.585  |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1