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ViT5_1024
anhdt-dsai-02/ViT5_1024
ViT5_1024 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 24, 2023
- Updated
- Nov 24, 2023
- SHA
- 68e818b9
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_1024
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: 0.5008
- Rouge-1: 0.3673
- Rouge-2: 0.2276
- Rouge-4: 0.1451
- Rouge-l: 0.3317
- Rouge-w-1.2: 0.1398
- Rouge-s4: 0.1853
- Rouge-su4: 0.2162
- R: 0.3044
- P: 0.463
- Bleu: 19.2804
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.5811 | 1.0 | 629 | 0.5152 | 0.2291 | 0.147 | 0.0963 | 0.2053 | 0.0868 | 0.1206 | 0.139 | 0.1836 | 0.3046 | 10.8017 |
| 0.5204 | 2.0 | 1258 | 0.5024 | 0.3559 | 0.2182 | 0.1371 | 0.3191 | 0.1355 | 0.1755 | 0.2061 | 0.2945 | 0.4495 | 18.7571 |
| 0.4607 | 3.0 | 1887 | 0.4984 | 0.3674 | 0.222 | 0.1374 | 0.329 | 0.1386 | 0.1787 | 0.2107 | 0.3108 | 0.4493 | 19.4123 |
| 0.4577 | 4.0 | 2516 | 0.5008 | 0.3673 | 0.2276 | 0.1451 | 0.3317 | 0.1398 | 0.1853 | 0.2162 | 0.3044 | 0.463 | 19.2804 |
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 24, 2023
- Updated
- Nov 24, 2023