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my_summarize_vi
duwuonline/my_summarize_vi
my_summarize_vi is a machine learning model from duwuonline. 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
- Aug 22, 2023
- Updated
- Aug 23, 2023
- SHA
- ef504d29
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. -->
my_summarize_vi
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: 0.7072
- Rouge1: 0.2541
- Rouge2: 0.1945
- Rougel: 0.2328
- Rougelsum: 0.233
- Gen Len: 19.0
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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- 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 | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 1.0682 | 1.0 | 801 | 0.6850 | 0.252 | 0.1922 | 0.2305 | 0.2304 | 19.0 |
| 0.7129 | 2.0 | 1602 | 0.6764 | 0.2515 | 0.1862 | 0.2273 | 0.2274 | 19.0 |
| 0.5657 | 3.0 | 2403 | 0.6899 | 0.2553 | 0.1959 | 0.2334 | 0.2335 | 19.0 |
| 0.4963 | 4.0 | 3204 | 0.7072 | 0.2541 | 0.1945 | 0.2328 | 0.233 | 19.0 |
Framework versions
- Transformers 4.32.0
- Pytorch 2.0.0
- Datasets 2.14.4
- Tokenizers 0.13.3
- Library
- transformers
- Type
- t5
- License
- mit
- Created
- Aug 22, 2023
- Updated
- Aug 23, 2023