---
license: apache-2.0
base_model: google/flan-t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: flan-t5-small-lamp-4u-finetuned-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. -->

# flan-t5-small-lamp-4u-finetuned-3

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: 2.4088
- Rouge1: 0.1634
- Rouge2: 0.0510
- Rougel: 0.1494
- Rougelsum: 0.1500

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
| 2.6388        | 1.0   | 1566  | 2.5235          | 0.1413 | 0.0452 | 0.1311 | 0.1316    |
| 2.5039        | 2.0   | 3132  | 2.4539          | 0.1469 | 0.0474 | 0.1354 | 0.1359    |
| 2.401         | 3.0   | 4698  | 2.4320          | 0.1525 | 0.0486 | 0.1409 | 0.1414    |
| 2.3748        | 4.0   | 6264  | 2.4193          | 0.1528 | 0.0495 | 0.1414 | 0.1417    |
| 2.2997        | 5.0   | 7830  | 2.4120          | 0.1559 | 0.0490 | 0.1427 | 0.1430    |
| 2.2742        | 6.0   | 9396  | 2.4042          | 0.1562 | 0.0508 | 0.1436 | 0.1438    |
| 2.2404        | 7.0   | 10962 | 2.4039          | 0.1584 | 0.0515 | 0.1457 | 0.1461    |
| 2.2249        | 8.0   | 12528 | 2.4010          | 0.1624 | 0.0509 | 0.1491 | 0.1495    |
| 2.1985        | 9.0   | 14094 | 2.3993          | 0.1622 | 0.0520 | 0.1493 | 0.1501    |
| 2.1509        | 10.0  | 15660 | 2.3993          | 0.1599 | 0.0505 | 0.1454 | 0.1462    |
| 2.1226        | 11.0  | 17226 | 2.4026          | 0.1631 | 0.0519 | 0.1498 | 0.1503    |
| 2.107         | 12.0  | 18792 | 2.4040          | 0.1623 | 0.0513 | 0.1487 | 0.1491    |
| 2.0855        | 13.0  | 20358 | 2.4049          | 0.1634 | 0.0517 | 0.1493 | 0.1498    |
| 2.0678        | 14.0  | 21924 | 2.4028          | 0.1631 | 0.0515 | 0.1489 | 0.1495    |
| 2.0899        | 15.0  | 23490 | 2.4052          | 0.1628 | 0.0510 | 0.1489 | 0.1496    |
| 2.0777        | 16.0  | 25056 | 2.4050          | 0.1628 | 0.0503 | 0.1493 | 0.1498    |
| 2.0572        | 17.0  | 26622 | 2.4076          | 0.1620 | 0.0511 | 0.1481 | 0.1488    |
| 2.0408        | 18.0  | 28188 | 2.4066          | 0.1625 | 0.0510 | 0.1487 | 0.1495    |
| 2.0538        | 19.0  | 29754 | 2.4076          | 0.1635 | 0.0510 | 0.1496 | 0.1503    |
| 2.0283        | 20.0  | 31320 | 2.4088          | 0.1634 | 0.0510 | 0.1494 | 0.1500    |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.0.1+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0