---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-small-finetune-cnn
  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-small-finetune-cnn

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: 1.9579
- Rouge1: 24.7426
- Rouge2: 10.4667
- Rougel: 20.2334
- Rougelsum: 23.0122
- 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.9721        | 1.0   | 2000  | 1.9608          | 25.1804 | 10.8327 | 20.5778 | 23.3974   | 19.0    |
| 1.9466        | 2.0   | 4000  | 1.9549          | 25.0152 | 10.6784 | 20.4465 | 23.2601   | 19.0    |
| 1.8932        | 3.0   | 6000  | 1.9515          | 25.0464 | 10.7024 | 20.3992 | 23.2249   | 19.0    |
| 1.8564        | 4.0   | 8000  | 1.9489          | 25.0313 | 10.642  | 20.3601 | 23.2032   | 19.0    |
| 1.862         | 5.0   | 10000 | 1.9510          | 24.9582 | 10.614  | 20.3625 | 23.1762   | 19.0    |
| 1.8478        | 6.0   | 12000 | 1.9502          | 25.032  | 10.7084 | 20.4506 | 23.2435   | 19.0    |
| 1.819         | 7.0   | 14000 | 1.9495          | 24.7874 | 10.4848 | 20.2893 | 23.0832   | 19.0    |
| 1.7869        | 8.0   | 16000 | 1.9470          | 24.7095 | 10.4465 | 20.1705 | 22.9248   | 19.0    |
| 1.8068        | 9.0   | 18000 | 1.9510          | 24.705  | 10.4407 | 20.1684 | 22.9817   | 19.0    |
| 1.768         | 10.0  | 20000 | 1.9517          | 24.6067 | 10.4281 | 20.0765 | 22.9034   | 19.0    |
| 1.7713        | 11.0  | 22000 | 1.9524          | 24.6871 | 10.4126 | 20.1802 | 22.962    | 19.0    |
| 1.7635        | 12.0  | 24000 | 1.9548          | 24.5998 | 10.3969 | 20.1427 | 22.9191   | 19.0    |
| 1.7625        | 13.0  | 26000 | 1.9561          | 24.66   | 10.4032 | 20.1732 | 22.9256   | 19.0    |
| 1.7461        | 14.0  | 28000 | 1.9551          | 24.7071 | 10.4209 | 20.1833 | 22.9803   | 19.0    |
| 1.7271        | 15.0  | 30000 | 1.9558          | 24.6682 | 10.4162 | 20.198  | 22.9445   | 19.0    |
| 1.7452        | 16.0  | 32000 | 1.9563          | 24.8148 | 10.4558 | 20.2123 | 23.0374   | 19.0    |
| 1.7489        | 17.0  | 34000 | 1.9576          | 24.6459 | 10.3782 | 20.1213 | 22.8918   | 19.0    |
| 1.724         | 18.0  | 36000 | 1.9581          | 24.7384 | 10.427  | 20.2088 | 22.9971   | 19.0    |
| 1.7236        | 19.0  | 38000 | 1.9581          | 24.7366 | 10.4394 | 20.2028 | 23.0286   | 19.0    |
| 1.7331        | 20.0  | 40000 | 1.9579          | 24.7426 | 10.4667 | 20.2334 | 23.0122   | 19.0    |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3