---
library_name: transformers
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
datasets:
- big_patent
metrics:
- rouge
model-index:
- name: my_T5_summarization_model
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: big_patent
      type: big_patent
      config: f
      split: validation
      args: f
    metrics:
    - name: Rouge1
      type: rouge
      value: 0.2277
---

<!-- 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. -->

# my_T5_summarization_model

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the big_patent dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9477
- Rouge1: 0.2277
- Rouge2: 0.1286
- Rougel: 0.1988
- Rougelsum: 0.1988
- 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: 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: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.156         | 1.0   | 5348  | 2.0181          | 0.2264 | 0.1267 | 0.1971 | 0.1972    | 19.0    |
| 2.1095        | 2.0   | 10696 | 1.9737          | 0.227  | 0.1276 | 0.1977 | 0.1978    | 19.0    |
| 2.0867        | 3.0   | 16044 | 1.9545          | 0.2277 | 0.1285 | 0.1987 | 0.1988    | 19.0    |
| 2.0577        | 4.0   | 21392 | 1.9477          | 0.2277 | 0.1286 | 0.1988 | 0.1988    | 19.0    |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1