---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: results_t5base
  results: []
pipeline_tag: summarization
---

<!-- 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. -->

# results_t5base

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3660
- Rouge1: 0.904
- Rouge2: 0.8349
- Rougel: 0.8863
- Gen Len: 237.7528

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Gen Len  |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:--------:|
| 0.6675        | 0.8969 | 200  | 0.5012          | 0.8797 | 0.7929 | 0.8578 | 236.6854 |
| 0.5426        | 1.7937 | 400  | 0.4133          | 0.8937 | 0.8192 | 0.8751 | 237.7101 |
| 0.2768        | 2.6906 | 600  | 0.3971          | 0.8984 | 0.8262 | 0.8797 | 237.7551 |
| 0.4136        | 3.5874 | 800  | 0.3864          | 0.9001 | 0.8295 | 0.8824 | 237.7483 |
| 0.3067        | 4.4843 | 1000 | 0.3815          | 0.9011 | 0.8307 | 0.8833 | 237.7506 |
| 0.4425        | 5.3812 | 1200 | 0.3735          | 0.9015 | 0.8319 | 0.884  | 237.7528 |
| 0.4285        | 6.2780 | 1400 | 0.3720          | 0.9026 | 0.8334 | 0.885  | 237.7528 |
| 0.3025        | 7.1749 | 1600 | 0.3687          | 0.9039 | 0.8345 | 0.8859 | 237.7528 |
| 0.2699        | 8.0717 | 1800 | 0.3681          | 0.9034 | 0.8341 | 0.8857 | 237.7528 |
| 0.4072        | 8.9686 | 2000 | 0.3657          | 0.9039 | 0.8349 | 0.8862 | 237.7528 |
| 0.4555        | 9.8655 | 2200 | 0.3660          | 0.904  | 0.8349 | 0.8863 | 237.7528 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1