---
license: apache-2.0
base_model: yazdipour/text-to-sparql-t5-small-qald9
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: text-to-sparql-t5-small-qald9
  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. -->

# text-to-sparql-t5-small-qald9

This model is a fine-tuned version of [yazdipour/text-to-sparql-t5-small-qald9](https://huggingface.co/yazdipour/text-to-sparql-t5-small-qald9) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0001
- Gen Len: 19.0
- P: 0.6665
- R: 0.1769
- F1: 0.4085
- Bleu-score: 12.0496
- Bleu-precisions: [98.39650145772595, 98.13559322033899, 97.77327935222672, 97.23618090452261]
- Bleu-bp: 0.1231

## 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: 0.0003
- 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
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Gen Len | P      | R      | F1     | Bleu-score | Bleu-precisions                                                              | Bleu-bp |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:------:|:------:|:----------:|:----------------------------------------------------------------------------:|:-------:|
| No log        | 1.0   | 28   | 0.2187          | 19.0    | 0.5442 | 0.1725 | 0.3510 | 9.1204     | [84.10326086956522, 63.125, 53.49264705882353, 45.75892857142857]            | 0.1519  |
| No log        | 2.0   | 56   | 0.0265          | 19.0    | 0.6848 | 0.1878 | 0.4229 | 9.2726     | [97.80907668231612, 94.84346224677716, 93.73601789709173, 92.02279202279202] | 0.0980  |
| No log        | 3.0   | 84   | 0.0092          | 19.0    | 0.6648 | 0.1744 | 0.4063 | 11.7575    | [97.9502196193265, 97.10391822827938, 96.5376782077393, 95.69620253164557]   | 0.1214  |
| No log        | 4.0   | 112  | 0.0055          | 19.0    | 0.6571 | 0.1701 | 0.4004 | 12.1496    | [97.40259740259741, 95.97989949748744, 95.20958083832335, 94.07407407407408] | 0.1270  |
| No log        | 5.0   | 140  | 0.0023          | 19.0    | 0.6654 | 0.1752 | 0.4070 | 11.8546    | [98.09941520467837, 97.44897959183673, 96.95121951219512, 96.21212121212122] | 0.1220  |
| No log        | 6.0   | 168  | 0.0010          | 19.0    | 0.6665 | 0.1769 | 0.4085 | 12.0496    | [98.39650145772595, 98.13559322033899, 97.77327935222672, 97.23618090452261] | 0.1231  |
| No log        | 7.0   | 196  | 0.0008          | 19.0    | 0.6665 | 0.1769 | 0.4085 | 12.0496    | [98.39650145772595, 98.13559322033899, 97.77327935222672, 97.23618090452261] | 0.1231  |
| No log        | 8.0   | 224  | 0.0003          | 19.0    | 0.6665 | 0.1769 | 0.4085 | 12.0496    | [98.39650145772595, 98.13559322033899, 97.77327935222672, 97.23618090452261] | 0.1231  |
| No log        | 9.0   | 252  | 0.0005          | 19.0    | 0.6665 | 0.1769 | 0.4085 | 12.0496    | [98.39650145772595, 98.13559322033899, 97.77327935222672, 97.23618090452261] | 0.1231  |
| No log        | 10.0  | 280  | 0.0002          | 19.0    | 0.6665 | 0.1769 | 0.4085 | 12.0496    | [98.39650145772595, 98.13559322033899, 97.77327935222672, 97.23618090452261] | 0.1231  |
| No log        | 11.0  | 308  | 0.0002          | 19.0    | 0.6665 | 0.1769 | 0.4085 | 12.0496    | [98.39650145772595, 98.13559322033899, 97.77327935222672, 97.23618090452261] | 0.1231  |
| No log        | 12.0  | 336  | 0.0001          | 19.0    | 0.6665 | 0.1769 | 0.4085 | 12.0496    | [98.39650145772595, 98.13559322033899, 97.77327935222672, 97.23618090452261] | 0.1231  |
| No log        | 13.0  | 364  | 0.0002          | 19.0    | 0.6665 | 0.1769 | 0.4085 | 12.0496    | [98.39650145772595, 98.13559322033899, 97.77327935222672, 97.23618090452261] | 0.1231  |
| No log        | 14.0  | 392  | 0.0001          | 19.0    | 0.6665 | 0.1769 | 0.4085 | 12.0496    | [98.39650145772595, 98.13559322033899, 97.77327935222672, 97.23618090452261] | 0.1231  |
| No log        | 15.0  | 420  | 0.0001          | 19.0    | 0.6665 | 0.1769 | 0.4085 | 12.0496    | [98.39650145772595, 98.13559322033899, 97.77327935222672, 97.23618090452261] | 0.1231  |
| No log        | 16.0  | 448  | 0.0001          | 19.0    | 0.6665 | 0.1769 | 0.4085 | 12.0496    | [98.39650145772595, 98.13559322033899, 97.77327935222672, 97.23618090452261] | 0.1231  |
| No log        | 17.0  | 476  | 0.0001          | 19.0    | 0.6665 | 0.1769 | 0.4085 | 12.0496    | [98.39650145772595, 98.13559322033899, 97.77327935222672, 97.23618090452261] | 0.1231  |
| 0.088         | 18.0  | 504  | 0.0001          | 19.0    | 0.6665 | 0.1769 | 0.4085 | 12.0496    | [98.39650145772595, 98.13559322033899, 97.77327935222672, 97.23618090452261] | 0.1231  |
| 0.088         | 19.0  | 532  | 0.0001          | 19.0    | 0.6665 | 0.1769 | 0.4085 | 12.0496    | [98.39650145772595, 98.13559322033899, 97.77327935222672, 97.23618090452261] | 0.1231  |
| 0.088         | 20.0  | 560  | 0.0001          | 19.0    | 0.6665 | 0.1769 | 0.4085 | 12.0496    | [98.39650145772595, 98.13559322033899, 97.77327935222672, 97.23618090452261] | 0.1231  |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2