---
library_name: transformers
license: apache-2.0
base_model: t5-small
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-small-finetuned-stock-news-3
  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-finetuned-stock-news-3

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: 0.5388
- Rouge1: 46.5843
- Rouge2: 39.8053
- Rougel: 45.0579
- Rougelsum: 45.1153

## 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: 4e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 0.6486        | 1.0   | 2061  | 0.5804          | 46.121  | 39.3055 | 44.5881 | 44.6641   |
| 0.5558        | 2.0   | 4122  | 0.5550          | 46.3546 | 39.6639 | 44.9562 | 44.9928   |
| 0.518         | 3.0   | 6183  | 0.5472          | 46.6276 | 39.8816 | 45.1918 | 45.251    |
| 0.4974        | 4.0   | 8244  | 0.5384          | 46.6196 | 39.7899 | 45.0584 | 45.1347   |
| 0.4794        | 5.0   | 10305 | 0.5385          | 46.6275 | 39.7555 | 45.0597 | 45.1392   |
| 0.4714        | 6.0   | 12366 | 0.5388          | 46.5843 | 39.8053 | 45.0579 | 45.1153   |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.1
- Tokenizers 0.21.1