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ViT5
anhdt-dsai-02/ViT5
ViT5 is a machine learning model from anhdt-dsai-02. 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 mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- mit
- Model type
- t5
- Access
- Public
- Created
- Nov 21, 2023
- Updated
- Nov 24, 2023
- SHA
- 57991ce2
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. -->
ViT5
This model is a fine-tuned version of VietAI/vit5-base-vietnews-summarization on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5754671692848206
- Rouge-1: 0.2966
- Rouge-2: 0.1572
- Rouge-4: 0.0899
- Rouge-l: 0.2582
- Rouge-w-1.2: 0.1046
- Rouge-s4: 0.1182
- Rouge-su4: 0.1485
- R: 0.2336
- P: 0.4058
- Bleu: 12.7017
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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge-1 | Rouge-2 | Rouge-4 | Rouge-l | Rouge-w-1.2 | Rouge-s4 | Rouge-su4 | R | P | Bleu |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6619 | 1.0 | 628 | 0.6740 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.67 | 2.0 | 1256 | 0.6519 | 0.2971 | 0.1722 | 0.1027 | 0.2659 | 0.1072 | 0.1353 | 0.1628 | 0.2169 | 0.4713 | 11.5398 |
| 0.5606 | 3.0 | 1884 | 0.6481 | 0.3067 | 0.1597 | 0.0794 | 0.2693 | 0.1064 | 0.1184 | 0.1504 | 0.2311 | 0.4557 | 10.4569 |
| 0.5006 | 4.0 | 2512 | 0.6499 | 0.3029 | 0.1619 | 0.0815 | 0.2663 | 0.1051 | 0.1193 | 0.1504 | 0.229 | 0.4474 | 10.9827 |
Framework versions
- Transformers 4.26.1
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
- Library
- transformers
- Type
- t5
- License
- mit
- Created
- Nov 21, 2023
- Updated
- Nov 24, 2023