transformers tensorboard safetensors t5 text2text-generation generated_from_trainer base_model:t5-base license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
---
license: apache-2.0
base_model: t5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: T5_base_title_v4
  results: []
---

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# T5_base_title_v4

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: 1.6697
- Rouge1: 0.4305
- Rouge2: 0.2304
- Rougel: 0.3728
- Rougelsum: 0.3729
- Gen Len: 16.6586

## 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: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.9653        | 1.0   | 2019  | 1.7927          | 0.4092 | 0.2145 | 0.3528 | 0.3528    | 16.6021 |
| 1.828         | 2.0   | 4038  | 1.7374          | 0.4148 | 0.217  | 0.3557 | 0.3558    | 16.7601 |
| 1.7597        | 3.0   | 6057  | 1.7053          | 0.4183 | 0.2199 | 0.3595 | 0.3594    | 16.8878 |
| 1.6787        | 4.0   | 8076  | 1.6875          | 0.4221 | 0.224  | 0.3649 | 0.3647    | 16.6098 |
| 1.6361        | 5.0   | 10095 | 1.6730          | 0.4227 | 0.2229 | 0.3655 | 0.3657    | 16.6044 |
| 1.6032        | 6.0   | 12114 | 1.6679          | 0.4266 | 0.227  | 0.3696 | 0.3697    | 16.4617 |
| 1.5701        | 7.0   | 14133 | 1.6657          | 0.4265 | 0.2273 | 0.3694 | 0.3692    | 16.4184 |
| 1.5359        | 8.0   | 16152 | 1.6677          | 0.4273 | 0.2274 | 0.3695 | 0.3695    | 16.5704 |
| 1.5136        | 9.0   | 18171 | 1.6639          | 0.4271 | 0.2278 | 0.3697 | 0.3697    | 16.5989 |
| 1.4776        | 10.0  | 20190 | 1.6641          | 0.4291 | 0.2297 | 0.3723 | 0.3722    | 16.5137 |
| 1.4507        | 11.0  | 22209 | 1.6650          | 0.4307 | 0.2303 | 0.372  | 0.3718    | 16.5868 |
| 1.437         | 12.0  | 24228 | 1.6654          | 0.4277 | 0.2274 | 0.3711 | 0.3711    | 16.7277 |
| 1.4428        | 13.0  | 26247 | 1.6689          | 0.4296 | 0.2287 | 0.3714 | 0.3715    | 16.7078 |
| 1.4183        | 14.0  | 28266 | 1.6697          | 0.4307 | 0.2301 | 0.3726 | 0.3725    | 16.6979 |
| 1.4244        | 15.0  | 30285 | 1.6697          | 0.4305 | 0.2304 | 0.3728 | 0.3729    | 16.6586 |


### Framework versions

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