transformers safetensors t5 text2text-generation generated_from_trainer dataset:tiagoblima/du-qg-squadv1_pt base_model:unicamp-dl/ptt5-base-portuguese-vocab license:mit autotrain_compatible endpoints_compatible text-generation-inference region:us
---
license: mit
base_model: unicamp-dl/ptt5-base-portuguese-vocab
tags:
- generated_from_trainer
datasets:
- tiagoblima/du-qg-squadv1_pt
model-index:
- name: t5_base-qg-ap-test
  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_base-qg-ap-test

This model is a fine-tuned version of [unicamp-dl/ptt5-base-portuguese-vocab](https://huggingface.co/unicamp-dl/ptt5-base-portuguese-vocab) on the tiagoblima/du-qg-squadv1_pt dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0163

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
- lr_scheduler_type: linear
- num_epochs: 100.0

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 1    | 12.8054         |
| No log        | 2.0   | 2    | 10.7880         |
| No log        | 3.0   | 3    | 8.8731          |
| No log        | 4.0   | 4    | 7.4068          |
| No log        | 5.0   | 5    | 6.4581          |
| No log        | 6.0   | 6    | 5.6475          |
| No log        | 7.0   | 7    | 4.9596          |
| No log        | 8.0   | 8    | 4.5058          |
| No log        | 9.0   | 9    | 4.0768          |
| No log        | 10.0  | 10   | 3.7047          |
| No log        | 11.0  | 11   | 3.4143          |
| No log        | 12.0  | 12   | 3.1360          |
| No log        | 13.0  | 13   | 2.8866          |
| No log        | 14.0  | 14   | 2.6325          |
| No log        | 15.0  | 15   | 2.3889          |
| No log        | 16.0  | 16   | 2.1914          |
| No log        | 17.0  | 17   | 2.0424          |
| No log        | 18.0  | 18   | 1.9111          |
| No log        | 19.0  | 19   | 1.7763          |
| No log        | 20.0  | 20   | 1.6505          |
| No log        | 21.0  | 21   | 1.5257          |
| No log        | 22.0  | 22   | 1.4126          |
| No log        | 23.0  | 23   | 1.3109          |
| No log        | 24.0  | 24   | 1.2189          |
| No log        | 25.0  | 25   | 1.1338          |
| No log        | 26.0  | 26   | 1.0486          |
| No log        | 27.0  | 27   | 0.9640          |
| No log        | 28.0  | 28   | 0.8828          |
| No log        | 29.0  | 29   | 0.8060          |
| No log        | 30.0  | 30   | 0.7329          |
| No log        | 31.0  | 31   | 0.6639          |
| No log        | 32.0  | 32   | 0.6010          |
| No log        | 33.0  | 33   | 0.5439          |
| No log        | 34.0  | 34   | 0.4925          |
| No log        | 35.0  | 35   | 0.4471          |
| No log        | 36.0  | 36   | 0.4066          |
| No log        | 37.0  | 37   | 0.3690          |
| No log        | 38.0  | 38   | 0.3341          |
| No log        | 39.0  | 39   | 0.3023          |
| No log        | 40.0  | 40   | 0.2746          |
| No log        | 41.0  | 41   | 0.2470          |
| No log        | 42.0  | 42   | 0.2205          |
| No log        | 43.0  | 43   | 0.1968          |
| No log        | 44.0  | 44   | 0.1771          |
| No log        | 45.0  | 45   | 0.1593          |
| No log        | 46.0  | 46   | 0.1424          |
| No log        | 47.0  | 47   | 0.1288          |
| No log        | 48.0  | 48   | 0.1170          |
| No log        | 49.0  | 49   | 0.1070          |
| No log        | 50.0  | 50   | 0.0996          |
| No log        | 51.0  | 51   | 0.0939          |
| No log        | 52.0  | 52   | 0.0888          |
| No log        | 53.0  | 53   | 0.0845          |
| No log        | 54.0  | 54   | 0.0818          |
| No log        | 55.0  | 55   | 0.0790          |
| No log        | 56.0  | 56   | 0.0763          |
| No log        | 57.0  | 57   | 0.0732          |
| No log        | 58.0  | 58   | 0.0697          |
| No log        | 59.0  | 59   | 0.0666          |
| No log        | 60.0  | 60   | 0.0642          |
| No log        | 61.0  | 61   | 0.0611          |
| No log        | 62.0  | 62   | 0.0583          |
| No log        | 63.0  | 63   | 0.0560          |
| No log        | 64.0  | 64   | 0.0532          |
| No log        | 65.0  | 65   | 0.0512          |
| No log        | 66.0  | 66   | 0.0487          |
| No log        | 67.0  | 67   | 0.0464          |
| No log        | 68.0  | 68   | 0.0431          |
| No log        | 69.0  | 69   | 0.0399          |
| No log        | 70.0  | 70   | 0.0381          |
| No log        | 71.0  | 71   | 0.0364          |
| No log        | 72.0  | 72   | 0.0348          |
| No log        | 73.0  | 73   | 0.0333          |
| No log        | 74.0  | 74   | 0.0316          |
| No log        | 75.0  | 75   | 0.0299          |
| No log        | 76.0  | 76   | 0.0285          |
| No log        | 77.0  | 77   | 0.0274          |
| No log        | 78.0  | 78   | 0.0264          |
| No log        | 79.0  | 79   | 0.0253          |
| No log        | 80.0  | 80   | 0.0242          |
| No log        | 81.0  | 81   | 0.0236          |
| No log        | 82.0  | 82   | 0.0231          |
| No log        | 83.0  | 83   | 0.0229          |
| No log        | 84.0  | 84   | 0.0226          |
| No log        | 85.0  | 85   | 0.0223          |
| No log        | 86.0  | 86   | 0.0218          |
| No log        | 87.0  | 87   | 0.0212          |
| No log        | 88.0  | 88   | 0.0205          |
| No log        | 89.0  | 89   | 0.0198          |
| No log        | 90.0  | 90   | 0.0192          |
| No log        | 91.0  | 91   | 0.0186          |
| No log        | 92.0  | 92   | 0.0181          |
| No log        | 93.0  | 93   | 0.0177          |
| No log        | 94.0  | 94   | 0.0173          |
| No log        | 95.0  | 95   | 0.0170          |
| No log        | 96.0  | 96   | 0.0168          |
| No log        | 97.0  | 97   | 0.0166          |
| No log        | 98.0  | 98   | 0.0165          |
| No log        | 99.0  | 99   | 0.0164          |
| 1.4009        | 100.0 | 100  | 0.0163          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.0.0
- Datasets 2.15.0
- Tokenizers 0.15.0
