---
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: tidy-tab-model-t5-small
  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. -->

# tidy-tab-model-t5-small

This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9997
- Rouge1: 0.7404
- Rouge2: 0.6249
- Rougel: 0.7403
- Rougelsum: 0.7413
- Gen Len: 6.9017

## 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: 5e-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
- lr_scheduler_warmup_steps: 1000
- num_epochs: 32

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.3461        | 3.7879  | 500  | 1.0711          | 0.7407 | 0.6192 | 0.736  | 0.7374    | 7.188   |
| 1.0075        | 7.5758  | 1000 | 0.9645          | 0.7313 | 0.6071 | 0.7304 | 0.7303    | 6.9274  |
| 0.7921        | 11.3636 | 1500 | 0.9563          | 0.7306 | 0.6079 | 0.7323 | 0.7325    | 6.7863  |
| 0.6587        | 15.1515 | 2000 | 0.9697          | 0.7382 | 0.6142 | 0.739  | 0.7397    | 6.8675  |
| 0.5579        | 18.9394 | 2500 | 0.9905          | 0.7388 | 0.6203 | 0.7378 | 0.7395    | 6.8718  |
| 0.4984        | 22.7273 | 3000 | 0.9997          | 0.7404 | 0.6249 | 0.7403 | 0.7413    | 6.9017  |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1