---
library_name: transformers
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
datasets:
- xsum
metrics:
- rouge
model-index:
- name: outputs-project-id2223
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: xsum
      type: xsum
      config: default
      split: validation
      args: default
    metrics:
    - name: Rouge1
      type: rouge
      value: 31.3824
---

<!-- 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. -->

# outputs-project-id2223

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the xsum dataset.
It achieves the following results on the evaluation set:
- Gen Len: 19.7143
- Loss: 2.2606
- Rouge1: 31.3824
- Rouge2: 9.9473
- Rougel: 24.9422
- Rougelsum: 24.9453

## 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: Use 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Gen Len | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum |
|:-------------:|:-----:|:------:|:-------:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 2.6596        | 1.0   | 12753  | 19.6937 | 2.4320          | 29.2361 | 8.3218 | 22.9893 | 22.9993   |
| 2.5914        | 2.0   | 25506  | 19.7058 | 2.3844          | 29.8093 | 8.7641 | 23.5074 | 23.5169   |
| 2.5171        | 4.0   | 51012  | 19.6821 | 2.3208          | 30.6455 | 9.3612 | 24.2744 | 24.2798   |
| 2.4813        | 6.0   | 76518  | 19.6813 | 2.2865          | 31.1312 | 9.7512 | 24.6686 | 24.6688   |
| 2.4517        | 7.0   | 89271  | 19.7118 | 2.2757          | 31.1544 | 9.7509 | 24.6982 | 24.7016   |
| 2.449         | 9.0   | 114777 | 19.7143 | 2.2606          | 31.3824 | 9.9473 | 24.9422 | 24.9453   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0