---
license: apache-2.0
base_model: t5-base
tags:
- generated_from_trainer
datasets:
- arrow
model-index:
- name: text-to-sparql-t5-base-2024-09-01_11-28
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/padole/huggingface/runs/ca910scu)
# text-to-sparql-t5-base-2024-09-01_11-28

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: 0.1292
- Gen Len: 19.0
- Bertscorer-p: 0.6002
- Bertscorer-r: 0.1065
- Bertscorer-f1: 0.3419
- Sacrebleu-score: 6.1640
- Sacrebleu-precisions: [92.31534063748829, 84.93160766667017, 79.6643621245387, 75.5827850229174]
- Bleu-bp: 0.0744

## 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: 1
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------------:|:------------:|:-------------:|:---------------:|:--------------------------------------------------------------------------:|:-------:|
| 0.1458        | 1.0   | 4772 | 0.1292          | 19.0    | 0.6002       | 0.1065       | 0.3419        | 6.1640          | [92.31534063748829, 84.93160766667017, 79.6643621245387, 75.5827850229174] | 0.0744  |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1