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wikinews_t5-small
drive087/wikinews_t5-small
wikinews_t5-small is a machine learning model from drive087. 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
- Mar 8, 2023
- Updated
- Mar 8, 2023
- SHA
- b0064097
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. -->
wikinews_model
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0753
- Rouge1: 0.2105
- Rouge2: 0.1842
- Rougel: 0.2105
- Rougelsum: 0.2105
- Gen Len: 9.3158
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: 8
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5000
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 0.7014 | 35.71 | 500 | 0.6265 | 0.2675 | 0.1316 | 0.2675 | 0.2675 | 9.3684 |
| 0.3433 | 71.43 | 1000 | 0.7564 | 0.2807 | 0.1579 | 0.2807 | 0.2807 | 9.7895 |
| 0.2291 | 107.14 | 1500 | 0.9650 | 0.2632 | 0.1842 | 0.2632 | 0.2632 | 9.5 |
| 0.1626 | 142.86 | 2000 | 1.0753 | 0.2105 | 0.1842 | 0.2105 | 0.2105 | 9.3158 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Mar 8, 2023
- Updated
- Mar 8, 2023