Downloads · 30 days
8
24% of all-time downloads
text-to-sparql-Version-3.5
Uzair54/text-to-sparql-Version-3.5
text-to-sparql-Version-3.5 is a machine learning model from Uzair54. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
All-time downloads
34
Public
Parameters
60.5M
484 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors242 MB · 99%
At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- t5
- Access
- Public
- Created
- Jun 9, 2024
- Updated
- Jun 9, 2024
- SHA
- 1dcfdd1f
Base models
Model card
From the Hugging Face model README
<!-- 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-Version-3.5
This model is a fine-tuned version of yazdipour/text-to-sparql-t5-small-qald9 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0689
- Gen Len: 19.0
- Bleu-score: 0.3061
- Bleu-precisions: [91.41630901287553, 82.88177339901478, 72.54335260115607, 64.86013986013987]
- Bleu-bp: 0.0040
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Gen Len | Bleu-score | Bleu-precisions | Bleu-bp |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 18 | 0.9058 | 19.0 | 0.3206 | [77.68014059753955, 42.92730844793713, 18.040089086859687, 6.298200514138817] | 0.0129 |
| No log | 2.0 | 36 | 0.3255 | 19.0 | 0.1908 | [85.59046587215602, 65.37982565379825, 42.60614934114202, 29.129662522202487] | 0.0037 |
| No log | 3.0 | 54 | 0.1637 | 19.0 | 0.1969 | [89.16478555304741, 76.76240208877284, 62.538699690402474, 55.32319391634981] | 0.0028 |
| No log | 4.0 | 72 | 0.1002 | 19.0 | 0.2395 | [91.40022050716648, 79.41550190597205, 66.11694152923538, 57.22120658135283] | 0.0033 |
| No log | 5.0 | 90 | 0.0761 | 19.0 | 0.2712 | [91.28540305010893, 81.57894736842105, 70.64896755162242, 62.18637992831541] | 0.0036 |
| No log | 6.0 | 108 | 0.0689 | 19.0 | 0.3061 | [91.41630901287553, 82.88177339901478, 72.54335260115607, 64.86013986013987] | 0.0040 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Jun 9, 2024
- Updated
- Jun 9, 2024