---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-small-asqa-ob
  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. -->

# t5-small-asqa-ob

This model is a fine-tuned version of [google/t5-small-ssm-nq](https://huggingface.co/google/t5-small-ssm-nq) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9381
- Rouge1: 0.1633
- Rouge2: 0.0907
- Rougel: 0.1394
- Rougelsum: 0.1393

## 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: 0.0005
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
| 3.8212        | 1.0   | 710   | 2.7920          | 0.1248 | 0.0624 | 0.1064 | 0.1063    |
| 3.0559        | 2.0   | 1420  | 2.5937          | 0.1319 | 0.0715 | 0.1139 | 0.1138    |
| 2.568         | 3.0   | 2130  | 2.4971          | 0.1398 | 0.0754 | 0.1206 | 0.1204    |
| 2.384         | 4.0   | 2840  | 2.5024          | 0.1473 | 0.0817 | 0.1273 | 0.1271    |
| 2.1599        | 5.0   | 3550  | 2.4947          | 0.1498 | 0.0824 | 0.1288 | 0.1287    |
| 2.0444        | 6.0   | 4260  | 2.5305          | 0.1502 | 0.0837 | 0.1291 | 0.1290    |
| 1.9219        | 7.0   | 4970  | 2.5486          | 0.1599 | 0.0890 | 0.1376 | 0.1373    |
| 1.7532        | 8.0   | 5680  | 2.5772          | 0.1647 | 0.0914 | 0.1413 | 0.1411    |
| 1.6895        | 9.0   | 6390  | 2.6346          | 0.1630 | 0.0911 | 0.1397 | 0.1395    |
| 1.5751        | 10.0  | 7100  | 2.6650          | 0.1700 | 0.0944 | 0.1450 | 0.1449    |
| 1.4616        | 11.0  | 7810  | 2.6705          | 0.1571 | 0.0874 | 0.1348 | 0.1346    |
| 1.3923        | 12.0  | 8520  | 2.7767          | 0.1695 | 0.0951 | 0.1453 | 0.1450    |
| 1.3043        | 13.0  | 9230  | 2.8091          | 0.1704 | 0.0943 | 0.1460 | 0.1457    |
| 1.2868        | 14.0  | 9940  | 2.8390          | 0.1553 | 0.0854 | 0.1327 | 0.1324    |
| 1.176         | 15.0  | 10650 | 2.9381          | 0.1633 | 0.0907 | 0.1394 | 0.1393    |


### Framework versions

- Transformers 4.23.0.dev0
- Pytorch 1.12.1+cu102
- Datasets 2.5.1
- Tokenizers 0.12.1