---
library_name: transformers
license: apache-2.0
base_model: t5-base
tags:
- generated_from_trainer
datasets:
- arrow
model-index:
- name: text-to-sparql-t5-base-2024-10-01_04-05
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# text-to-sparql-t5-base-2024-10-01_04-05

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the arrow dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1612
- Gen Len: 19.0
- Bertscorer-p: 0.6042
- Bertscorer-r: 0.1007
- Bertscorer-f1: 0.3406
- Sacrebleu-score: 6.3972
- Sacrebleu-precisions: [93.50202971813725, 87.89528553225993, 83.9093099978942, 81.08246812206387]
- Bleu-bp: 0.0740

## 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Gen Len | Bertscorer-p | Bertscorer-r | Bertscorer-f1 | Sacrebleu-score | Sacrebleu-precisions                                                         | Bleu-bp |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------------:|:------------:|:-------------:|:---------------:|:----------------------------------------------------------------------------:|:-------:|
| 0.1434        | 1.0   | 4772  | 0.1290          | 19.0    | 0.5779       | 0.0743       | 0.3142        | 5.8962          | [92.35991566894258, 84.39366674829903, 78.94400227401933, 75.86961452759951] | 0.0713  |
| 0.0942        | 2.0   | 9544  | 0.1177          | 19.0    | 0.5888       | 0.0849       | 0.3250        | 6.1087          | [92.5606800784706, 85.52426907082315, 80.69350019995765, 77.57006871168893]  | 0.0728  |
| 0.0653        | 3.0   | 14316 | 0.1173          | 19.0    | 0.6046       | 0.1056       | 0.3434        | 6.3214          | [93.2540100046867, 86.96274167420529, 82.274102896671, 78.77417998317914]    | 0.0742  |
| 0.0483        | 4.0   | 19088 | 0.1232          | 19.0    | 0.5986       | 0.0961       | 0.3355        | 6.2622          | [93.15494173500215, 86.84532601814729, 82.2615628114192, 79.1214879303522]   | 0.0735  |
| 0.0334        | 5.0   | 23860 | 0.1311          | 19.0    | 0.6023       | 0.0994       | 0.3390        | 6.3073          | [93.43068494727854, 87.49234763885077, 83.1708833292281, 80.1232645304334]   | 0.0734  |
| 0.0235        | 6.0   | 28632 | 0.1357          | 19.0    | 0.6001       | 0.0980       | 0.3372        | 6.3131          | [93.21137315406656, 87.16716210233382, 82.85332802379921, 79.83819964161484] | 0.0737  |
| 0.0168        | 7.0   | 33404 | 0.1473          | 19.0    | 0.6041       | 0.1033       | 0.3419        | 6.4057          | [93.29664975783108, 87.43513246633191, 83.24213326488467, 80.18603064651553] | 0.0746  |
| 0.0119        | 8.0   | 38176 | 0.1505          | 19.0    | 0.6012       | 0.0990       | 0.3382        | 6.3570          | [93.1113662456946, 87.19629610143632, 83.0426651081239, 80.06573325445343]   | 0.0742  |
| 0.0088        | 9.0   | 42948 | 0.1542          | 19.0    | 0.6055       | 0.1041       | 0.3430        | 6.4203          | [93.41891452713682, 87.77185624336455, 83.69605828507379, 80.74261780654649] | 0.0744  |
| 0.0071        | 10.0  | 47720 | 0.1612          | 19.0    | 0.6042       | 0.1007       | 0.3406        | 6.3972          | [93.50202971813725, 87.89528553225993, 83.9093099978942, 81.08246812206387]  | 0.0740  |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 3.0.0
- Tokenizers 0.19.1