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

# flan-t5-s

This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2736
- Rouge1: 40.152
- Rouge2: 15.8816
- Rougel: 33.4399
- Rougelsum: 35.9029
- Gen Len: 19.886

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 0.347         | 1.0   | 2307  | 0.2918          | 38.3203 | 14.7065 | 31.7739 | 34.536    | 19.904  |
| 0.2765        | 2.0   | 4615  | 0.2817          | 38.9417 | 15.3147 | 32.5082 | 35.1789   | 19.884  |
| 0.2683        | 3.0   | 6922  | 0.2776          | 39.3458 | 15.3133 | 32.7661 | 35.2993   | 19.878  |
| 0.2635        | 4.0   | 9230  | 0.2751          | 39.7671 | 15.7051 | 33.1173 | 35.6438   | 19.884  |
| 0.2611        | 5.0   | 11537 | 0.2738          | 39.8607 | 15.5855 | 33.1643 | 35.6319   | 19.882  |
| 0.2592        | 6.0   | 13842 | 0.2736          | 40.152  | 15.8816 | 33.4399 | 35.9029   | 19.886  |


### Framework versions

- Transformers 4.36.1
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.15.2