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t5-small-asqp-rest16
arus05/t5-small-asqp-rest16
t5-small-asqp-rest16 is a machine learning model from arus05. 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. --
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At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- t5
- Access
- Public
- Created
- Jul 2, 2025
- Updated
- Jul 2, 2025
- SHA
- 3b295342
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. -->
t5-small-asqp-rest16
This model is a fine-tuned version of google-t5/t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3935
- Precision: 0.4913
- Recall: 0.501
- F1: 0.4961
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
|---|---|---|---|---|---|---|
| No log | 1.0 | 79 | 0.4778 | 0.286 | 0.2821 | 0.284 |
| No log | 2.0 | 158 | 0.3743 | 0.3683 | 0.3669 | 0.3676 |
| No log | 3.0 | 237 | 0.3512 | 0.3757 | 0.3905 | 0.383 |
| No log | 4.0 | 316 | 0.3440 | 0.4416 | 0.4398 | 0.4407 |
| No log | 5.0 | 395 | 0.3573 | 0.4306 | 0.4714 | 0.4501 |
| No log | 6.0 | 474 | 0.3668 | 0.4228 | 0.4536 | 0.4377 |
| 0.5075 | 7.0 | 553 | 0.3718 | 0.4457 | 0.4773 | 0.461 |
| 0.5075 | 8.0 | 632 | 0.3754 | 0.4586 | 0.4813 | 0.4697 |
| 0.5075 | 9.0 | 711 | 0.3778 | 0.4865 | 0.499 | 0.4927 |
| 0.5075 | 10.0 | 790 | 0.3774 | 0.4813 | 0.4832 | 0.4823 |
| 0.5075 | 11.0 | 869 | 0.3895 | 0.509 | 0.501 | 0.505 |
| 0.5075 | 12.0 | 948 | 0.3910 | 0.4834 | 0.4892 | 0.4863 |
| 0.1367 | 13.0 | 1027 | 0.3920 | 0.4875 | 0.499 | 0.4932 |
| 0.1367 | 14.0 | 1106 | 0.3901 | 0.4863 | 0.4892 | 0.4877 |
| 0.1367 | 15.0 | 1185 | 0.3935 | 0.4913 | 0.501 | 0.4961 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Jul 2, 2025
- Updated
- Jul 2, 2025