---
license: apache-2.0
base_model: t5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: T5_base_title_v2
  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_v2

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: 2.0995
- Rouge1: 0.3574
- Rouge2: 0.1666
- Rougel: 0.3037
- Rougelsum: 0.303
- Gen Len: 16.495

## 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   | 100  | 2.1695          | 0.3249 | 0.1495 | 0.2795 | 0.2798    | 17.315  |
| No log        | 2.0   | 200  | 2.0994          | 0.3595 | 0.1696 | 0.3078 | 0.3085    | 16.825  |
| No log        | 3.0   | 300  | 2.0724          | 0.3679 | 0.1836 | 0.312  | 0.3131    | 16.525  |
| No log        | 4.0   | 400  | 2.0745          | 0.3669 | 0.1767 | 0.3137 | 0.3141    | 16.505  |
| 2.0908        | 5.0   | 500  | 2.0567          | 0.3725 | 0.181  | 0.3205 | 0.3211    | 16.545  |
| 2.0908        | 6.0   | 600  | 2.0575          | 0.3654 | 0.174  | 0.3101 | 0.3097    | 16.62   |
| 2.0908        | 7.0   | 700  | 2.0640          | 0.3475 | 0.1649 | 0.2959 | 0.2956    | 16.485  |
| 2.0908        | 8.0   | 800  | 2.0588          | 0.3678 | 0.1827 | 0.312  | 0.3113    | 16.54   |
| 2.0908        | 9.0   | 900  | 2.0615          | 0.3654 | 0.1774 | 0.3106 | 0.3098    | 16.565  |
| 1.696         | 10.0  | 1000 | 2.0689          | 0.3654 | 0.1767 | 0.3077 | 0.3069    | 16.78   |
| 1.696         | 11.0  | 1100 | 2.0767          | 0.3633 | 0.1736 | 0.309  | 0.3078    | 16.57   |
| 1.696         | 12.0  | 1200 | 2.0749          | 0.366  | 0.1802 | 0.3147 | 0.3145    | 16.755  |
| 1.696         | 13.0  | 1300 | 2.0782          | 0.3632 | 0.1714 | 0.3117 | 0.3111    | 16.95   |
| 1.696         | 14.0  | 1400 | 2.0841          | 0.3637 | 0.1718 | 0.3118 | 0.3111    | 16.855  |
| 1.5311        | 15.0  | 1500 | 2.0873          | 0.3618 | 0.1713 | 0.3073 | 0.307     | 16.57   |
| 1.5311        | 16.0  | 1600 | 2.0940          | 0.3655 | 0.1714 | 0.3115 | 0.3111    | 16.625  |
| 1.5311        | 17.0  | 1700 | 2.0943          | 0.3619 | 0.1683 | 0.3089 | 0.3082    | 16.525  |
| 1.5311        | 18.0  | 1800 | 2.0981          | 0.3609 | 0.1697 | 0.3074 | 0.3065    | 16.44   |
| 1.5311        | 19.0  | 1900 | 2.0990          | 0.3567 | 0.1665 | 0.3047 | 0.3036    | 16.47   |
| 1.447         | 20.0  | 2000 | 2.0995          | 0.3574 | 0.1666 | 0.3037 | 0.303     | 16.495  |


### Framework versions

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