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finetuned-news_summarization_vi
minhquy1624/finetuned-news_summarization_vi
finetuned-news_summarization_vi is a machine learning model from minhquy1624. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- License
- mit
- Model type
- t5
- Access
- Public
- Created
- Aug 18, 2024
- Updated
- Aug 19, 2024
- SHA
- 0f26394f
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. -->
finetuned-news_summarization_vi
This model is a fine-tuned version of VietAI/vit5-large-vietnews-summarization on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2271
- Rouge1: 0.253
- Rouge2: 0.1919
- Rougel: 0.2233
- Rougelsum: 0.2233
- Gen Len: 18.496
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: 1
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 0.2561 | 1.0 | 65361 | 0.2342 | 0.248 | 0.1883 | 0.2192 | 0.2192 | 18.274 |
| 0.1831 | 2.0 | 130722 | 0.2271 | 0.253 | 0.1919 | 0.2233 | 0.2233 | 18.496 |
Framework versions
- Transformers 4.43.1
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Type
- t5
- License
- mit
- Created
- Aug 18, 2024
- Updated
- Aug 19, 2024